Medical Imaging
medical imaging
MUV PhD Program
The Medical University of Vienna invites applications for all currently open PhD positions in its 18 PhD programs. Our university is a leader in transnational basic and applied (medicine) research and has an excellent infrastructure that invites you to do research, learn state-of-the-art methods and network with your fellow researchers. Our research community is international and constantly growing, as is our campus. Three more research buildings will be added in the next few years. Last but not least, Austria, as a research location, offers young scientists many opportunities after graduation. We currently offer up to 32 fully funded Ph.D. positions to ambitious and creative researchers with a background in (Bio) Physics, (Bio) Engineering, Mathematics, (Bio) Informatics, Computer Science, (Bio) Chemistry, Biology, Neuroscience, Immunology or Cell/Molecular biology or a related field to take their first steps as professional researchers with us. We offer - Interdisciplinary Ph.D. programme that gives you the freedom to tailor parts of your curriculum to suit your individual interests - Cutting-edge basic and applied (medical) research - Interesting projects and tasks - Like-minded colleagues - Supportive environment for personal and professional growth - Modern and highly specialised equipment, such as the Tesla7 - A triple-track system that allows easy access to patients (data) for clinical trials or user feedback - An international and well-connected research community - Advanced training and mentoring programmes - Live and work in one of the most liveable places - Vienna About us The Medical University of Vienna (briefly: MedUni Vienna) was founded in 1365 and is now the largest medical university in Europe with about 8.000 students. Within its 30 university hospital departments, two clinical institutes, one museum, 12 theoretical medicine centres and numerous highly specialized laboratories, it is included among the most important cutting-edge research institutes of Europe in the area of biomedicine and biotechnology. Terms The initial contract of the Ph.D. is limited to one year and can be extended until the end of the training (three to four years). The salary is based either on the Austrian collective agreement for university employees and researchers or on the FWF salary agreement. An individual start date is a possibility. Application information Online application portal: https://oc.meduniwien.ac.at/open-positions Questions? Contact us at phdrecruitment@muv.ac.at
MedUni PhD Recruitment
Medical University of Vienna invites applications for all currently open Ph.D. positions within their 18 Ph.D. programs. We encourage ambitious and creative young scientists to develop their original research project in the field of Behavioural Biology, Biochemistry, Biophysics, Bioinformatics & Machine Learning, Cancer, Cardiovascular Systems, Drug Targets & Drug Development, Endocrinology & Metabolism, Biomedical Engineering, Mathematics & Statistics, Immunology, Medical Physics, Mental Health, Molecular and Cellular Biology, Neuroscience and Public Health with the assistance of our renowned and international scientists . Benefit from a well-established and connected network within the science community and built important relations with your peers at our university. On top of it, become an expert in your field! All project information can be found online under https://www.meduniwien.ac.at/web/en/studies-further-education/phd-doctoral-programmes/phd-programme-un094/phd-opportunities/ Apply online till 20.11.2022
Departement of Movement Sciences, KU Leuven
We are looking for a dynamic and motivated individual (m/f) with an excellent research record in studying the human brain and motor behavior by means of multimodal medical techniques (such as MRI, movement registration, EEG, etc.). We offer a full-time employment in an intellectually challenging environment. KU Leuven is a research-intensive, internationally oriented university that promotes both fundamental and applied scientific research. It is highly focused on inter- and multidisciplinary research and strives for international excellence. It provides its students with an academic education that is based on high-quality scientific research. KU Leuven aims for transparent and reproducible research. You will work in Leuven, a historic, dynamic and lively city located in the heart of Belgium, within 20 minutes from Brussels, the capital of the European Union, and less than two hours from Paris, London and Amsterdam. Depending on your record and qualifications, you will be appointed to or tenured in one of the grades of the senior academic staff: assistant professor, associate professor, professor or full professor. In principle, junior researchers are appointed as assistant professor on the tenure track for a period of 5 years; after this period and contingent upon a positive evaluation, they are permanently appointed (or tenured) as associate professor. KU Leuven is well set to welcome foreign professors and their family and provides practical support with regard to immigration & administration, housing, childcare, learning Dutch, partner career coaching, … Vacancy: https://www.kuleuven.be/personeel/jobsite/jobs/55675790?hl=en&lang=en
Prof. Dr. Dr. Daniel Alexander Braun
There is a fully funded PhD position available at the Institute of Neural Information Processing, Ulm University, Germany. At the institute we are interested in the mathematical foundations of intelligent behaviour in biological and artificial systems. The PhD topic will revolve around the fundamental question of how the abstraction capabilities of classic symbolic knowledge systems can be combined with the sub-symbolic pattern recognition capabilities of neural networks in order to allow neural networks to take existing knowledge into account when making predictions. The PhD position will be part of the newly established DFG graduate school KEMAI (Knowledge Infusion and Extraction for Explainable Medical AI). The structured PhD programme has a duration of 3 years with the possibility of extending for one more year. The candidate will have the opportunity both to make contributions to fundamental questions in AI and cognitive science and to apply their work directly in the context of medical imaging through collaboration with Ulm University Clinic. Within the same broad topic area there is a second PhD position available at the Institute of Medical Systems Biology that includes investigation of genetic markers.
Constantine Dovrolis
Development of new ML methods for medical imaging, particularly for cancer detection.
Georgios Exarchakis
The University of Bath invites applications for a fully-funded PhD position in Machine Learning, as part of the prestigious URSA competition. This project focuses on developing interpretable machine learning methods for high-dimensional data, with an emphasis on recognizing symmetries and incorporating them into efficient, flexible algorithms. This PhD position offers the opportunity to work within a leading research environment, using state-of-the-art tools such as TensorFlow, PyTorch, and Scikit-Learn. The research outcomes have potential applications in diverse fields, and students are encouraged to bring creative and interdisciplinary approaches to problem-solving.
Georg Langs
We are recruiting for a tenure-track Assistant Professor position in the area „Machine Learning in the Life Sciences“ at Medical University of Vienna. The position will be a group leader at the new Comprehensive Center of AI in Medicine (CAIM) that will start in January 2025 at MedUni Vienna. It will be a dual appointment at CAIM and another Department at MedUni Wien that the candidate can choose. CAIM will bring together ML researchers and labs from across the university at one physical place. Currently, about 15 labs are involved that will build the starting point of the center. MedUni will nominate the successful candidate in a Viennese Research Group Call for a EUR 1.8 Mio startup research budget.
Sometimes more is not better: The case of medical imaging
En el diagnóstico médico por imágenes muchas veces los desarrollos técnicos se han concentrado en mejorar la calidad de las imágenes en términos de resolución espacial y/o temporal, lo cual muchas veces ha incrementado considerablemente los costos de estas prestaciones. Sin embargo, mejor resolución espacial y/o temporal de las imágenes médicas, no se traducen necesariamente en mejores diagnósticos o en diagnósticos más tempranos, y en algunos casos, nuevas capacidades diagnósticas no han demostrado un impacto en reducir la mortalidad asociada a las patologías. En esta presentación discutiremos como el impacto de las nuevas tecnologías en salud debe ser medido en términos del resultado clínico del paciente o la población afectada más que en parámetros asociados a la "calidad" de las imágenes.
Preclinical fMRI: Why should we care and what it's useful for
Learning with less labels for medical image segmentation
Accurate segmentation of medical images is a key step in developing Computer-Aided Diagnosis (CAD) and automating various clinical tasks such as image-guided interventions. The success of state-of-the-art methods for medical image segmentation is heavily reliant upon the availability of a sizable amount of labelled data. If the required quantity of labelled data for learning cannot be reached, the technology turns out to be fragile. The principle of consensus tells us that as humans, when we are uncertain how to act in a situation, we tend to look to others to determine how to respond. In this webinar, Dr Mehrtash Harandi will show how to model the principle of consensus to learn to segment medical data with limited labelled data. In doing so, we design multiple segmentation models that collaborate with each other to learn from labelled and unlabelled data collectively.
PET imaging in brain diseases
Talk 1. PET based biomarkers of treatment efficacy in temporal lobe epilepsy A critical aspect of drug development involves identifying robust biomarkers of treatment response for use as surrogate endpoints in clinical trials. However, these biomarkers also have the capacity to inform mechanisms of disease pathogenesis and therapeutic efficacy. In this webinar, Dr Bianca Jupp will report on a series of studies using the GABAA PET ligand, [18F]-Flumazenil, to establish biomarkers of treatment response to a novel therapeutic for temporal lobe epilepsy, identifying affinity at this receptor as a key predictor of treatment outcome. Dr Bianca Jupp is a Research Fellow in the Department of Neuroscience, Monash University and Lead PET/CT Scientist at the Alfred Research Alliance–Monash Biomedical Imaging facility. Her research focuses on neuroimaging and its capacity to inform the neurobiology underlying neurological and neuropsychiatric disorders. Talk 2. The development of a PET radiotracer for reparative microglia Imaging of neuroinflammation is currently hindered by the technical limitations associated with TSPO imaging. In this webinar, Dr Lucy Vivash will discuss the development of PET radiotracers that specifically image reparative microglia through targeting the receptor kinase MerTK. This includes medicinal chemistry design and testing, radiochemistry, and in vitro and in vivo testing of lead tracers. Dr Lucy Vivash is a Research Fellow in the Department of Neuroscience, Monash University. Her research focuses on the preclinical development and clinical translation of novel PET radiotracers for the imaging of neurodegenerative diseases.
Growing a world-class precision medicine industry
Monash Biomedical Imaging is part of the new $71.2 million Australian Precision Medicine Enterprise (APME) facility, which will deliver large-scale development and manufacturing of precision medicines and theranostic radiopharmaceuticals for industry and research. A key feature of the APME project is a high-energy cyclotron with multiple production clean rooms, which will be located on the Monash Biomedical Imaging (MBI) site in Clayton. This strategic co-location will facilitate radiochemistry, PET and SPECT research and clinical use of theranostic (therapeutic and diagnostic) radioisotopes produced on-site. In this webinar, MBI’s Professor Gary Egan and Dr Maggie Aulsebrook will explain how the APME will secure Australia’s supply of critical radiopharmaceuticals, build a globally competitive Australian manufacturing hub, and train scientists and engineers for the Australian workforce. They will cover the APME’s state-of-the-art 30 MeV and 18-24 MeV cyclotrons and radiochemistry facilities, as well as the services that will be accessible to students, scientists, clinical researchers, and pharmaceutical companies in Australia and around the world. The APME is a collaboration between Monash University, Global Medical Solutions Australia, and Telix Pharmaceuticals. Professor Gary Egan is Director of Monash Biomedical Imaging, Director of the ARC Centre of Excellence for Integrative Brain Function and a Distinguished Professor at the Turner Institute for Brain and Mental Health, Monash University. He is also lead investigator of the Victorian Biomedical Imaging Capability, and Deputy Director of the Australian National Imaging Facility. Dr Maggie Aulsebrook obtained her PhD in Chemistry at Monash University and specialises in the development and clinical translation of radiopharmaceuticals. She has led the development of several investigational radiopharmaceuticals for first-in-human application. Maggie leads the Radiochemistry Platform at Monash Biomedical Imaging.
MBI Webinar on preclinical research into brain tumours and neurodegenerative disorders
WEBINAR 1 Breaking the barrier: Using focused ultrasound for the development of targeted therapies for brain tumours presented by Dr Ekaterina (Caty) Salimova, Monash Biomedical Imaging Glioblastoma multiforme (GBM) - brain cancer - is aggressive and difficult to treat as systemic therapies are hindered by the blood-brain barrier (BBB). Focused ultrasound (FUS) - a non-invasive technique that can induce targeted temporary disruption of the BBB – is a promising tool to improve GBM treatments. In this webinar, Dr Ekaterina Salimova will discuss the MRI-guided FUS modality at MBI and her research to develop novel targeted therapies for brain tumours. Dr Ekaterina (Caty) Salimova is a Research Fellow in the Preclinical Team at Monash Biomedical Imaging. Her research interests include imaging cardiovascular disease and MRI-guided focused ultrasound for investigating new therapeutic targets in neuro-oncology. - WEBINAR 2 Disposition of the Kv1.3 inhibitory peptide HsTX1[R14A], a novel attenuator of neuroinflammation presented by Sanjeevini Babu Reddiar, Monash Institute of Pharmaceutical Sciences The voltage-gated potassium channel (Kv1.3) in microglia regulates membrane potential and pro-inflammatory functions, and non-selective blockade of Kv1.3 has shown anti-inflammatory and disease improvement in animal models of Alzheimer’s and Parkinson’s diseases. Therefore, specific inhibitors of pro-inflammatory microglial processes with CNS bioavailability are urgently needed, as disease-modifying treatments for neurodegenerative disorders are lacking. In this webinar, PhD candidate Ms Sanju Reddiar will discuss the synthesis and biodistribution of a Kv1.3-inhibitory peptide using a [64Cu]Cu-DOTA labelled conjugate. Sanjeevini Babu Reddiar is a PhD student at the Monash Institute of Pharmaceutical Sciences. She is working on a project identifying the factors governing the brain disposition and blood-brain barrier permeability of a Kv1.3-blocking peptide.
Monash Biomedical Imaging highlights from 2021 and looking ahead to 2022
Despite the challenges COVID-19 has continued to present, Monash Biomedical Imaging (MBI) has had another outstanding year in terms of publications and scientific output. In this webinar, Professor Gary Egan, Director of MBI, will present an overview of MBI’s achievements during 2021 and outline the biomedical imaging research programs and partnerships in 2022. His presentation will cover: • MBI operational and research achievements during 2021 • Biomedical imaging technology developments and research outcomes during 2021 • Linked laboratories and research teams at MBI • Progress on the development of a cyclotron and precision radiopharmaceutical facility at Clayton • Emerging research opportunities at the Monash Heart Hospital in cardiology and cardiovascular disease. Professor Gary Egan is Director of Monash Biomedical Imaging, Director of the ARC Centre of Excellence for Integrative Brain Function and a Distinguished Professor at the Turner Institute for Brain and Mental Health, Monash University. He is also lead investigator of the Victorian Biomedical Imaging Capability, and Deputy Director of the Australian National Imaging Facility. His substantive body of published work has made a significant impact on the neuroimaging and neuroscience fields. He has sustained success in obtaining significant grants to support his own research and the development of facilities to advance biomedical imaging.
Identification and treatment of advanced, rupture-prone plaques to reduce cardiovascular mortality
Atherosclerosis is the underlying cause of major cardiovascular events, including heart attack and stroke. The build-up of plaque in coronary arteries can be a major risk for events, but risk is significantly higher in patients with vulnerable rather than stable plaque. Diagnostic imaging of vulnerable plaque is extremely useful for both stratifying patient risk and for determining effectiveness of experimental intervention in reducing cardiovascular risk. In the preclinical setting, being able to distinguish between stable and vulnerable plaque development and pair this with biochemical measures is critical for identification of new experimental candidates. In this webinar, Professor Stephen Nicholls and Dr Kristen Bubb from the Victorian Heart Institute will discuss the benefits of being able to visualise vulnerable plaque for both clinical and preclinical research. Professor Stephen Nicholls is a clinician-researcher and the Head of the Victorian Heart Institute. He is the lead investigator on multiple large, international, cardiovascular outcomes trials. He has attracted over $100 million in direct research funding and published more than 400 peer-reviewed manuscripts. He is focused on both therapeutic intervention to reduce vascular inflammation and lipid accumulation and precision medicine approaches to prevent cardiovascular mortality. Dr Kristen Bubb is a biomedical researcher and Group Leader within the Monash Biomedicine Discovery Institute Cardiovascular Program and Victorian Heart Institute. She focuses on preclinical/translational research into mechanisms underlying vascular pathologies including atherosclerosis and endothelium-driven hypertension within specific vascular systems, including pulmonary and pregnancy-induced. She has published >30 high impact papers in leading cardiovascular journals and attracted category 1&2 funding of >$750,000.
From aura to neuroinflammation: Has imaging resolved the puzzle of migraine pathophysiology?
In this talk I will present data from imaging studies that we have been conducting for the past 20 years trying to shed light on migraine physiopathology, from anatomical and functional MRI to positron emission tomography.
Neural mechanisms of altered states of consciousness under psychedelics
Interest in psychedelic compounds is growing due to their remarkable potential for understanding altered neural states and their breakthrough status to treat various psychiatric disorders. However, there are major knowledge gaps regarding how psychedelics affect the brain. The Computational Neuroscience Laboratory at the Turner Institute for Brain and Mental Health, Monash University, uses multimodal neuroimaging to test hypotheses of the brain’s functional reorganisation under psychedelics, informed by the accounts of hierarchical predictive processing, using dynamic causal modelling (DCM). DCM is a generative modelling technique which allows to infer the directed connectivity among brain regions using functional brain imaging measurements. In this webinar, Associate Professor Adeel Razi and PhD candidate Devon Stoliker will showcase a series of previous and new findings of how changes to synaptic mechanisms, under the control of serotonin receptors, across the brain hierarchy influence sensory and associative brain connectivity. Understanding these neural mechanisms of subjective and therapeutic effects of psychedelics is critical for rational development of novel treatments and for the design and success of future clinical trials. Associate Professor Adeel Razi is a NHMRC Investigator Fellow and CIFAR Azrieli Global Scholar at the Turner Institute of Brain and Mental Health, Monash University. He performs cross-disciplinary research combining engineering, physics, and machine-learning. Devon Stoliker is a PhD candidate at the Turner Institute for Brain and Mental Health, Monash University. His interest in consciousness and psychiatry has led him to investigate the neural mechanisms of classic psychedelic effects in the brain.
Seeing things clearly: Image understanding through hard-attention and reasoning with structured knowledges
In this talk, Jonathan aims to frame the current challenges of explainability and understanding in ML-driven approaches to image processing, and their potential solution through explicit inference techniques.
Understanding the role of prediction in sensory encoding
At any given moment the brain receives more sensory information than it can use to guide adaptive behaviour, creating the need for mechanisms that promote efficient processing of incoming sensory signals. One way in which the brain might reduce its sensory processing load is to encode successive presentations of the same stimulus in a more efficient form, a process known as neural adaptation. Conversely, when a stimulus violates an expected pattern, it should evoke an enhanced neural response. Such a scheme for sensory encoding has been formalised in predictive coding theories, which propose that recent experience establishes expectations in the brain that generate prediction errors when violated. In this webinar, Professor Jason Mattingley will discuss whether the encoding of elementary visual features is modulated when otherwise identical stimuli are expected or unexpected based upon the history of stimulus presentation. In humans, EEG was employed to measure neural activity evoked by gratings of different orientations, and multivariate forward modelling was used to determine how orientation selectivity is affected for expected versus unexpected stimuli. In mice, two-photon calcium imaging was used to quantify orientation tuning of individual neurons in the primary visual cortex to expected and unexpected gratings. Results revealed enhanced orientation tuning to unexpected visual stimuli, both at the level of whole-brain responses and for individual visual cortex neurons. Professor Mattingley will discuss the implications of these findings for predictive coding theories of sensory encoding. Professor Jason Mattingley is a Laureate Fellow and Foundation Chair in Cognitive Neuroscience at The University of Queensland. His research is directed toward understanding the brain processes that support perception, selective attention and decision-making, in health and disease.
Developing metal-based radiopharmaceuticals for imaging and therapy
Personalised medicine will be greatly enhanced with the introduction of new radiopharmaceuticals for the diagnosis and treatment of various cancers, as well as cardiovascular disease and brain disorders. The unprecedented interest in developing theranostic radiopharmaceuticals is mainly due to the recent clinical successes of radiometal-based products including: • 177LuDOTA-TATE (trade name Lutathera, FDA approved in 2018), a peptide-based tracer that is used for treating metastatic neuroendocrine tumours • Ga 68 PSMA-11 (FDA approved in 2020), a positron emission tomography agent for imaging prostate-specific membrane antigen positive lesions in men with prostate cancer. In this webinar, Dr Brett Paterson and PhD candidate Mr Cormac Kelderman will present their research on developing the chemistry and radiochemistry to produce new radiometal-based imaging and therapy agents. They will discuss the synthesis of new molecules, the optimisation of the radiochemistry, and results from preclinical evaluations. Dr Brett Paterson is a National Imaging Facility Fellow at Monash Biomedical Imaging and academic group leader in the School of Chemistry, Monash University. His research focuses on the development of radiochemistry and new radiopharmaceuticals. Cormac Kelderman is a PhD candidate under the supervision of Dr Brett Paterson in the School of Chemistry, Monash University. His research focuses on developing new bis(thiosemicarbazone) chelators for technetium-99m SPECT imaging.
Virtual launch and webinar: Magnetic Particle Imaging at Monash University
Magnetic Particle Imaging (MPI) is a new non-invasive imaging technique with significantly increased sensitivity over MRI and faster acquisition times than PET and MRI. The MPI capability at the Alfred Research Alliance - Monash Biomedical Imaging site in Melbourne, Australia, is the world’s first MPI system with Computed Tomography (CT) and Hyperthermia capabilities. It provides unique capabilities that open the door to cutting-edge opportunities for interdisciplinary projects in medical research, chemistry and biotechnology. The webinar will involve: * official launch of Magnetic Particle Imaging at Monash University * the MPI system supplier, Magnetic Insight, discussing the world first technology and its potential * presentations from key researchers outlining MPI applications and the benefits of utilising the technology.
Fragility of the human connectome across the lifespan
The human brain network architecture can reveal crucial aspects of brain function and dysfunction. The topology of this network (known as the connectome) is shaped by a trade-off between wiring cost and network efficiency, and it has highly connected hub regions playing a prominent role in many brain disorders. By studying a landscape of plausible brain networks that preserve the wiring cost, fragile and resilient hubs can be identified. In this webinar, Dr Leonardo Gollo and Dr James Pang from Monash University will discuss this approach across the lifespan and some of its implications for neurodevelopmental and neurodegenerative diseases. Dr Leonardo Gollo is a Senior Research Fellow at the Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University. He holds an ARC Future Fellowship and his research interests include brain modelling, systems neuroscience, and connectomics. Dr James Pang is a Research Fellow at the Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University. His research interests are on combining neuroimaging and biophysical modelling to better understand the mechanisms of brain function in health and disease.
Mapping the brain’s remaining terra incognita
In this webinar, Dr Ye Tian and A/Prof Andrew Zalesky will present new research on mapping the functional architecture of the human subcortex. They used 3T and 7T functional MRI from more than 1000 people to map one of the most detailed functional atlases of the human subcortex to date. Comprising four hierarchical scales, the new atlas reveals the complex topographic organisation of the subcortex, which dynamically adapts to changing cognitive demands. The atlas enables whole-brain mapping of connectomes and has been used to optimise targeting of deep brain stimulation. This joint work with Professors Michael Breakspear and Daniel Margulies was recently published in Nature Neuroscience. In the second part of the webinar, Dr Ye Tian will present her current research on the biological ageing of different body systems, including the human brain, in health and degenerative conditions. Conducted in more than 30,000 individuals, this research reveals associations between the biological ageing of different body systems. She will show the impact of lifestyle factors on ageing and how advanced ageing can predict the risk of mortality. Associate Professor Andrew Zalesky is a Principal Researcher with a joint appointment between the Faculties of Engineering and Medicine at The University of Melbourne. He currently holds a NHMRC Senior Research Fellowship and serves as Associate Editor for Brain Topography, Neuroimage Clinical and Network Neuroscience. Dr Zalesky is recognised for the novel tools that he has developed to analyse brain networks and their application to the study of neuropsychiatric disorders. Dr Ye Tian is a postdoctoral researcher at the Department of Psychiatry, University of Melbourne. She received her PhD from the University of Melbourne in 2020, during which she established the Melbourne Subcortex Atlas. Dr Tian is interested in understanding brain organisation and using brain imaging techniques to unveil neuropathology underpinning neuropsychiatric disorders.
A machine learning way to analyse white matter tractography streamlines / Application of artificial intelligence in correcting motion artifacts and reducing scan time in MRI
1. Embedding is all you need: A machine learning way to analyse white matter tractography streamlines - Dr Shenjun Zhong, Monash Biomedical Imaging Embedding white matter streamlines with various lengths into fixed-length latent vectors enables users to analyse them with general data mining techniques. However, finding a good embedding schema is still a challenging task as the existing methods based on spatial coordinates rely on manually engineered features, and/or labelled dataset. In this webinar, Dr Shenjun Zhong will discuss his novel deep learning model that identifies latent space and solves the problem of streamline clustering without needing labelled data. Dr Zhong is a Research Fellow and Informatics Officer at Monash Biomedical Imaging. His research interests are sequence modelling, reinforcement learning and federated learning in the general medical imaging domain. 2. Application of artificial intelligence in correcting motion artifacts and reducing scan time in MRI - Dr Kamlesh Pawar, Monash Biomedical imaging Magnetic Resonance Imaging (MRI) is a widely used imaging modality in clinics and research. Although MRI is useful it comes with an overhead of longer scan time compared to other medical imaging modalities. The longer scan times also make patients uncomfortable and even subtle movements during the scan may result in severe motion artifact in the images. In this seminar, Dr Kamlesh Pawar will discuss how artificial intelligence techniques can reduce scan time and correct motion artifacts. Dr Pawar is a Research Fellow at Monash Biomedical Imaging. His research interest includes deep learning, MR physics, MR image reconstruction and computer vision.
Biomedical Image and Genetic Data Analysis with machine learning; applications in neurology and oncology
In this presentation I will show the opportunities and challenges of big data analytics with AI techniques in medical imaging, also in combination with genetic and clinical data. Both conventional machine learning techniques, such as radiomics for tumor characterization, and deep learning techniques for studying brain ageing and prognosis in dementia, will be addressed. Also the concept of deep imaging, a full integration of medical imaging and machine learning, will be discussed. Finally, I will address the challenges of how to successfully integrate these technologies in daily clinical workflow.
Development and Application of PET Imaging for Dementia Research
Molecular imaging using Positron Emission Tomography (PET) has become a major biomedical imaging technology. Its application towards characterisation of biochemical processes in disease could enable early detection and diagnosis, development of novel therapies and treatment evaluation. The technology is underpinned by the use of imaging probes radiolabelled with short-lived radioisotopes which can be specific and selective for biological targets in vivo e.g. markers for receptors, protein deposits, enzymes and metabolism. My talk will focus on the increasing development and application of PET imaging to clinical research in neurodegenerative diseases, for which it can be applied to delineate and understand the various pathological components of these disorders.
Delineating Reward/Avoidance Decision Process in the Impulsive-compulsive Spectrum Disorders through a Probabilistic Reversal Learning Task
Impulsivity and compulsivity are behavioural traits that underlie many aspects of decision-making and form the characteristic symptoms of Obsessive Compulsive Disorder (OCD) and Gambling Disorder (GD). The neural underpinnings of aspects of reward and avoidance learning under the expression of these traits and symptoms are only partially understood. " "The present study combined behavioural modelling and neuroimaging technique to examine brain activity associated with critical phases of reward and loss processing in OCD and GD. " "Forty-two healthy controls (HC), forty OCD and twenty-three GD participants were recruited in our study to complete a two-session reinforcement learning (RL) task featuring a “probability switch (PS)” with imaging scanning. Finally, 39 HC (20F/19M, 34 yrs +/- 9.47), 28 OCD (14F/14M, 32.11 yrs ±9.53) and 16 GD (4F/12M, 35.53yrs ± 12.20) were included with both behavioural and imaging data available. The functional imaging was conducted by using 3.0-T SIEMENS MAGNETOM Skyra syngo MR D13C at Monash Biomedical Imaging. Each volume compromised 34 coronal slices of 3 mm thickness with 2000 ms TR and 30 ms TE. A total of 479 volumes were acquired for each participant in each session in an interleaved-ascending manner. " " The standard Q-learning model was fitted to the observed behavioural data and the Bayesian model was used for the parameter estimation. Imaging analysis was conducted using SPM12 (Welcome Department of Imaging Neuroscience, London, United Kingdom) in the Matlab (R2015b) environment. The pre-processing commenced with the slice timing, realignment, normalization to MNI space according to T1-weighted image and smoothing with a 8 mm Gaussian kernel. " " The frontostriatal brain circuit including the putamen and medial orbitofrontal (mOFC) were significantly more active in response to receiving reward and avoiding punishment compared to receiving an aversive outcome and missing reward at 0.001 with FWE correction at cluster level; While the right insula showed greater activation in response to missing rewards and receiving punishment. Compared to healthy participants, GD patients showed significantly lower activation in the left superior frontal and posterior cingulum at 0.001 for the gain omission. " " The reward prediction error (PE) signal was found positively correlated with the activation at several clusters expanding across cortical and subcortical region including the striatum, cingulate, bilateral insula, thalamus and superior frontal at 0.001 with FWE correction at cluster level. The GD patients showed a trend of decreased reward PE response in the right precentral extending to left posterior cingulate compared to controls at 0.05 with FWE correction. " " The aversive PE signal was negatively correlated with brain activity in regions including bilateral thalamus, hippocampus, insula and striatum at 0.001 with FWE correction. Compared with the control group, GD group showed an increased aversive PE activation in the cluster encompassing right thalamus and right hippocampus, and also the right middle frontal extending to the right anterior cingulum at 0.005 with FWE correction. " " Through the reversal learning task, the study provided a further support of the dissociable brain circuits for distinct phases of reward and avoidance learning. Also, the OCD and GD is characterised by aberrant patterns of reward and avoidance processing.