NEW! MICCAI Educational Challenge 2023 Materials

Finalist! Preprocessing MRI in Python


Anna Zapaishchykova, Benjamin H. Kann

Finalist! Introduction to Autoencoders


Marek Wodzinski

Finalist! Organizing a medical imaging challenge in 2020s: practical considerations


Khrystyna Faryna, Daan Schouten, Kiran Vaidhya Venkadesh, Gino Jansen, Anindo Saha, Bram van Ginneken

Finalist! A tour of biomedical image segmentation using deep learning


Pulkit Khandelwal

Finalist! Decoding Brain Connections: Exploring Neural Function Networks Through fMRI Graph Analysis


Mariem Touihri

Finalist! Transfer Learning through MobileNet and ResNet34


Ayush Garg

Podcasts with leading researchers working in AI for Medicine to help educate young researchers getting started


Jay Shah
Arizona State University

Preprocessing CT in Python


Anna Zapaishchykova, Benjamin H.Kann
Harvard Medical School

Mastering Deep Learning Architectures for Medical Semantic Segmentation: A Student's Journey


Carlotta Sophia Hölzle, Vanessa Gonzalez, Kai Standvoss, Nassir Navab
Technical University Munich

The U-Net Model


Mauricio Reyes, Aurelie Pahud, Zixin Shelley Shu
University of Bern

VTK and VMTK Deciphered: A Step-by-Step Tutorial and Hands-On MICCAI-inspired Example


Paula Feldman
Universidad Torcuato Di Tella

Intensity Normalization in Medical Imaging


Susanne Schmid, Wallace Souza Loss
University of Calgary

"AI Quest: The Black Box Chronicles": An educational quiz video game


Mauricio Reyes
University of Bern

Diffusion Model based Data Synthesis from Brain MRI: Application to Alzheimer’s Disease


Ke Chen, Ying Weng, Guokun Zuo, Tom Dening, Akram Hosseini
University of Nottingham Ningbo China

Explanative tutorial on research paper and its preliminaries


Ranjana Roy Chowdhury
IIT Ropar

Introduction to Diffusion Models


Huidong Xie, Weijie Gan
Yale, WUSTL

Fundamental concepts in Digital Image Processing


Manjunath K N
Manipal Academy of Higher Education

How to write a classification algorithm for your project in less than 5 minutes (ResNet & DenseNet)


Andrei Alexandru Mircea
Carol Davila University of Medicine and Pharmacy

Explainable Artificial Intelligence (XAI) in Medical Applications


Yiming Zhang and YIng Weng
University of Nottingham Ningbo China

Annotating Surgical Video Data with Label Studio


Yannik Frisch
TU Darmstadt, Software Campus, Zeiss Group

PhD life: things I had to learn and unlearn


Leonardo Ayala
German Cancer Research Center

Exploring AI-derived annotations in Imaging Data Commons (IDC)


Deepa Krishnaswamy, Andrey Fedorov
Brigham and Women's Hospital

A New Frontier in Medicine: 3D Scene Understanding in Surgical Data Science


Tony Danjun Wang, Lennart Bastian, Nassir Navab
Technical University of Munich

Echoes from the DataRealm


Lalith Sharan, Georgii Kostiuchik, Sandy Engelhardt
Heidelberg University Hospital

Tutorials on Segment Anything in Medical Images


Jun Ma, Feifei Li, Yuting He, Lin Han, Chenyu You, Bo Wang
University of Toronto

Generative AI in Medical Images


Vanshali Sharma
Indian Institute of Technology Guwahati, India

MICCAI Educational Challenge 2022 Materials

Capturing Uncertainty in Medical Image Segmentation


Vatsal Raina
University of Cambridge

Automating Medical Image Processing with 3D Slicer


Antoine Sanner
Technical University of Darmstadt

An Intuitive Grasp on Segmentation Metrics


Playout Clément, Richer Emmanuelle, and Lepetit-Aimon Gabriel
Polytechnique Montréal, Hôpital Maisonneuve-Rosemont

BENDER Series- BEst practices in medical imagiNg DEep leaRning


Mauricio Reyes, Yannick Suter, Alba Segura, Mike Muller, Amith Kamath
University of Bern

Why F1 score is not enough? (Demystifying AUC)


Arash Ash
ETS Montreal

MNIST Digit Classifier on the Web


Gia Ngo, Minh Nguyen, Benjamin Lee
Cornell University

Setting up a website and evaluation system for a clinical challenge


Lennart Paul, Vanessa,Gonzalez, Nassir Navab
Technical University of Munich

Post-hoc explainable AI algorithms review


Weina Jin
Simon Fraser University

Nuclear Medicine Physics Lecture Series


Arman Rahmim and Carlos Uribe
The University of British Columbia

How to "Hack" Proprietary AI Image Processing Software


Andreas Maier
Fau Erlangen-Nürnberg

Introduction to Medical Software (Coursera)


Xenophon Papademetris
Yale School of Medicine

Generally Nuanced Deep Learning Framework (GaNDLF): Classification Task


Garv Mehdiratta, Ujjwal Baid, and Spyridon Bakas
University of Pennsylvania

MICCAI Educational Challenge 2021 Materials

Maier Unleashed - Review Rant - Part 1


Andreas Maier
Friedrich-Alexander-Universität Erlangen-Nürnberg

How to use Dwave Quantum Annealer & example of network optimization for brain or protein networks

Alex Crimi
Sano, Center for Computational Medicine

A discovery dive into the world of evaluation — Do’s, don’ts and other considerations

Annika Reinke, Minu Tizabi, Carole Sudre
German Cancer Research Center, King's College London, University College London

Brain MRI Age Classification using Deep Learning


Vijay Iyer, Sameer Muckatira, Eshan Joshi, Maria Duarte Rosa, Julia Hoerner, Amith Kamath. Mathworks

An interactive introduction to Multiview Learning with Canonical Correlation Analysis and Partial Least Squares using cca-zoo

James Chapman
University College London

Cell Detection with Contour Proposal Networks


Eric Upschulte
Forschungzentrum Juelich

Introducing the generally nuanced DL framework Segmentation Challenge

Sarthak Pati and Siddhesh P. Thakur, et. al
UPenn, TU Munich, TU Darmstadt, Germany Intel Corporation, University of Zurich, University of Edinburgh

Learning the Effect of Registration Hyperparameters


Andrew Hoopes and Adrian Dalca
Harvard University

Image Registration with the VoxelMorph Framework


Adrian Dalca and Andrew Hoopes
Harvard University

Curating and Preprocessing of a Dataset for Medical Image Registration


Mattias Heinrich
University of Luebeck

Project Roadmap for X-Ray Classifiers



Solace Hussein and Ben Duvieusart
University of Oxford

Computed Tomography techniques for the evaluation of Intestine


Manjunath K N
Manipal Institute of Technology, India

Whole-brain Segmentation with FastSurfer - How to create simple, intuitive and understandable tutorials for DL based neuroimaging applications in Colab

Leonie Henschel and Martin Reuter
DZNE Germany

MEC 2020 Materials

• 1st Place! Introduction to Medical Image Registration with DeepReg, Between Old and New (Teaser Video)
  Nina Montana Brown, Yunguan Fu, Shaheer Saeed, Adrià Casamitjana, Zachary Baum, Rémi Delaunay, Qianye Yang, Alexander Grimwood, Zhe Min, Ester Bonmati, Tom Vercauteren, Matthew J. Clarkson and Yipeng Hu - University College London, InstaDeep & King's College London
• 2nd Place! An Introduction to SimpleITK (Teaser Video)
  Ziv Yaniv, Bradley C. Lowekamp and David T. Chen - National Institute of Allergy and Infectious Diseases, National Institutes of Health & Medical Science and Computing LLC.
• 3rd Place! How to Organize a Challenge –- Behind the Scenes (Teaser Video)
  Annika Reinke, Matthias Eisenmann, Laura Aguilera Saiz, Sinan Onogur, Leonardo Antonio Ayala Menjivar and Peter Maximilian Full - German Cancer Research Center (DKFZ) & University of Heidelberg
• Finalist Guitar and Musical MRI Concepts (Part 2) (Part 3) (Teaser Video)
  Jerry J. Battista - Western University
• Finalist Hands on Machine Learning Training -- HaMLeT (Teaser Video)
  Leon Weninger, Laxmi Gupta and Philipp Gräbel - RWTH Aachen University
• Finalist The Basic Augmented Reality Demo -- BARD (Teaser Video)
  Matt Clarkson, Steve Thompson, Ester Bonmati, Tom Dowrick, Yipeng Hu and Ann Blandford - University College of London
• Finalist Medical Imaging with Deep Learning Overview (Teaser Video)
  Joseph Paul Cohen - AIMI, Stanford University and Mila, Quebec AI Institute
• Finalist AutoBlog: Automatically Converting Research Videos to Blog Posts (Blog) (Teaser Video)
  Andreas Maier - Friedrich Alexander Universität Erlangen-Nürnberg
• Finalist Quality Control and Curation of MR Imaging Cohorts via MRQy With Applications to TCIA Datasets (Paper) (Teaser Video)
  Satish Viswanath, Sadri, AR, Janowczyk, A, Zou, R, Verma, R, Beig, N, Antunes, J, Madabhushi, A and Tiwari, P - Case Western Reserve University
• Finalist Containers For Collaboration: Using Docker to Share Your Software (GitHub) (Teaser Video)
  Eric Kerfoot - King's College London
• Finalist nnU-Net : The no-new-Net for Automatic Segmentation (GitHub) (Teaser Video)
  Prateek Gupta, Kumar T. Rajamani and Mattias P. Heinrich - Indian Institute of Information Technology & University of Lübeck
• Finalist Data Preprocessing and Augmentation Using TorchIO: A Tutorial (GitHub) (Teaser Video)
  Fernando Pérez-García - University College London
• Finalist Deep Learning Classification from Brain MRI: Application to Alzheimer’s Disease (Teaser Video)
  Elina Thibeau-Sutre, Mauricio Diaz-Melo, Alexandre Routier, Didier Dormont, Ninon Burgos and Olivier Colliot - Sorbonne University & Inria Paris
• Project Roadmap for X-Ray Classifiers: MICCAI Educational Challenge
  Solace Hussein and Benjamin Duvieusart - St. Peter's College, University of Oxford, Department of Engineering Science
• So you want to learn deep, but you don't have data? (Blog)
  Andreas Maier - Friedrich Alexander Universität Erlangen-Nürnberg
• Introduction to Virtual Circuits (Part 2) (Part 3) (Circuit Simulator)
  George Stetten - University of Pittsburgh
• Challenges in radiology image data analysis
  KN Manjunath - Manipal Academy of Higher Education
• 3 Steps Are All You Need to Achieve SOTA in MICCAI 2020 Thyroid Nodule Segmentation Challenge
  Jun Ma - Nanjing University of Science and Technology
• Coding a CNN for Medical Imaging using TensorFlow 2
  Esmitt Ramírez - Autonomous University of Barcelona (UaB)
• How to get started with deep learning using MRI data
  Divya Gaur - Technical University of Kaiserslautern
• Node-Based Shader Editor for Volume Rendering in WebGL
  Víctor Ubieto - University Pompeu Fabra
• Hierarchical Adversarial Domain Alignment (HADA) for Brain Graph Prediction (GitHub)
  Alaa Bessadok - Istanbul Technical University
• Graph Deep Learning (Blog)
  Andreas Maier, Florian Thamm - Friedrich Alexander Universität Erlangen-Nürnberg
• Model Selection, Overfitting and Regulzarization
  Roberto Medeiros de Souza - University of Calgary
• To Publish, or Not to Publish
  Omri Bar

MEC 2019 Materials

• 1st Place! Survival Analysis for Deep Learning
  Sebastian Pölsterl - Ludwig Maximilians Universität Munich
• 2nd Place! How to structure and write a research paper? / Case study: research paper deconstruction (Alternate Youku Link,Additional supplementary video, Alternate Youku Link)
  Islem Rekik - Istanbul Technical University
• 3rd Place! Project Roadmap for the Medical Imaging Student working with Deep Learning (PDF)
  Camila González - Technical University of Darmstadt
• Finalist SNAPPY Augmented Reality Tutorial
  Stephen Thompson - University College of London
• Finalist Skin Lesion Classification : An Educational Guide (PDF)
  Soham Mazumder, Tobias Czempiel - Technical University of Munich
• Finalist BrainPainter visualisation software (Source code, arXiv Paper)
  Razvan Marinescu - Massachusetts Institute of Technology
• Finalist A beginner’s guide to shape analysis using Deformetrica (PDF)
  Benoit Martin - Inria Paris, Institut du Cerveau et de la Moelle épinière, Inserm, CNRS, Sorbonne Université
• Loss Functions for Medical Image Segmentation: A Taxonomy
  Jun Ma - Nanjing University of Science and Technology
• Deep Learning Model Training and Visualization for Spinal Cord Segmentation
  King Chung Ho*, Ratna Sagari Grandhi*, William Speier, Corey Arnold - University of California Los Angeles
• BISCAR: a histological image bank of the human cardiovascular system
  Claudia Mazo Vargas - University College Dublin and Oncomark, University of Valle, University of Leon
• Automatic Identification of Loose Connective and Muscle Tissue
  Claudia Mazo Vargas - University College Dublin and Oncomark, University of Valle, University of Leon
• Automatic Classification of Epithelial Tissue
  Claudia Mazo Vargas - University College Dublin and Oncomark, University of Valle, University of Leon
• SNAPPY Tutorial on Software Development for Clinical Translation
  Stephen Thompson - University College of London
• Developing the research prototypes to a software product, a case study of medical imaging application
  Manjunath K N - Manipal Isntitute of Technology
• Intelligent Edge: Building a Skin Cancer Prediction App with Azure Machine Learning, CoreML & Xamarin
  Anusua Trivedi - Microsoft
• Building a Diabetic Retinopathy Prediction Application using Azure Machine Learning
  Anusua Trivedi - Microsoft
• Tutorial: Abdominal CT Image Synthesis with Variational Autoencoders using PyTorch
  Lasse Hansen, Maximilian Blendowski and Mattias P. Heinrich - University of Luebeck
• Analysis of longitudinal data made easy with Leaspy
  Igor Koval, Raphaël Couronné, Stanley Durrleman - Institut du Cerveau et de la Moelle épinière (ICM), Inserm, U 1127, CNRS, UMR 7225, Sorbonne Université, Inria, Hôpital de la Pitié Salpêtrière, Ecole Polytechnique
• Combining the power of PyTorch and NiftyNet
  Fernando Pérez-García - University College of London
• A Beginner's Guide For Machine Learning Engineers On Medical Imaging
  Varik Hoang - University of Washington Tacoma
• 3D U-Net Segmentation
  Varik Hoang - University of Washington Tacoma
• The Power of Checkpointing in Medical Imaging
  Upasana Bharadwaj - University of California San Francisco

Complete MEI Materials Library

MEC 2019   ·  MISS 2018   ·  MEC 2018   ·  MISS 2016   ·  MEC 2015 Winners

MISS 2014   ·  MEC 2014 Winners   ·  MEC 2014-2015 Entries

MISS 2018 Talks

• (01) - Andrea Vedaldi Universal, Unsupervised and Understandable Image Representations 1:19:40
• (02) - Daniel Rueckert Introduction into CNNs for medical imaging 1:14:40
• (03) - Daniel Rueckert Deep Learning for medical image reconstruction, super resolution and segmentation 1:17:27
• (04) - Trevor Darrell Adaptive and Explainable Artificial Intelligence 1:27:28
• (05) - Thomas Brox Dense correspondence estimation with deep learning and cross dataset generalization 1:34:22
• (06) - René Vidal Segmental Spatio Temporal Deep Networks for Discovering the Language of Surgery 1:05:24
• (07) - René Vidal Mathematics of Deep Learning part 2 1:06:22
• (08) - René Vidal Mathematics of Deep Learning part 1 45:44
• (09) - Michael Bronstein Geometric deep learning on graphs and manifolds 2:13:35
• (10) - Larry Zitnick The dark ages Object Recognition before Deep Learning 1:19:39
• (11) - Kevin Zhou Deep learning and beyond Medical image recognition, segmentation and parsing 1:15:17
• (12) - Julia Schnabel Medical Imaging meets Deep Learning Introduction and Motivation 25:05
• (13) - Julia Schnabel Medical image quality assessment using deep learning 43:34
• (14) - Ender Konukoglu Using deep learning as priors in generative models for medical image computing 56:31
• (15) - MISS 2018 6:01

MEC 2018 Materials

• Winner! Using NiftyNet to Train U-Net for Cell Segmentation
  Zach Eaton-Rosen - University College London
• Finalist BATMAN - Basic and Advanced Tractography with MRtrix for All Neurophiles
  Marlene Tahedl - University of Regensburg
• Finalist 3D Reconstruction of CT Colonography Models for VR/AR Applications using Free Software Tools
  Soraia Figueiredo Paulo, Nuno Figueiredo, Joaquim Armando Jorge and Daniel Simões Lopes - INESC-ID, Champalimaud Foundation and Universidade de Lisboa
• Finalist Tutorial for Developing Image-Guided Intervention Modules using 3D Slicer
  Golafsoun Ameri and Leah Groves - Western University
• Basics of Image Registration
  Iman Aganj - Massachusetts General Hospital, Harvard Medical School
• Volume and Surface Rendering of 3D Medical Datasets in Unity
  Soraia Figueiredo Paulo, Miguel Belo, Rafael Kuffner dos Anjos, Joaquim Armando Jorge, Daniel Simões Lopes - INESC-ID
• Medical Image Analysis Laboratory (MIALab): An Educational Approach to Medical Image Analysis using Machine Learning
  Fabian Balsiger, Alain Jungo, Yannick Suter, and Mauricio Reyes - University of Bern
• Object-Orientation and Design Patterns
  Eric Kerfoot - King's College London
• Let's cook a realistic brain for science
  Yiming Xiao
• Semi-automated pipeline for neuroimaging PET/MR visualization and quantification
  Fabio Raman - University of Alabama at Birmingham
• A Practical Guide to Statistical Shape Models Featuring Hands-on Examples in CONRAD
  Anna Gebhard, Tobias Geimer, Mathias Unberath, Frank Schebesch, Mena Abdelmalek - Friedrich-Alexander-Universität Erlangen-Nürnberg
• Hinge Loss, Support Vector Machines and the Loss of Users
  Andreas Maier, Vincent Christlein, Tobias Würfl, Katharina Breininger, Shahab Zarei - Friedrich-Alexander-Universität Erlangen-Nürnberg
• How to build a deep learning framework
  Katharina Breininger and Tobias Würfl - Friedrich-Alexander-University Erlangen-Nürnberg

MISS 2016 Talks

• (01) - MISS 2016 Favignana Spot 3:15
• (02) - Alison Noble (University of Oxford, United Kingdom) 1:05:14
• (03) - Carsten Rother (Technische Universität Dresden, Germany) 1:14:48
• (04) - Carsten Rother (Technische Universität Dresden, Germany) 46:52
• (05) - William M. Wells III (Harvard Medical School and MIT CSAIL, USA) 1:23:47
• (06) - Ben Glocker (Imperial College London, United Kingdom) 59:38
• (07) - Nicholas Ayache (INRIA, France) 1:39:05
• (08) - Marleen de Bruijne (University of Copenhagen, Denmark and Erasmus MC - University Medical Center Rotterdam, The Netherlands) 1:10:32
• (09) - Marleen de Bruijne University of Copenhagen, Denmark and Erasmus MC - University Medical Center Rotterdam, The Netherlands 50:36
• (10) - Ben Glocker (Imperial College London, United Kingdom) 1:05:35
• (11) - William M. Wells III (Harvard Medical School and MIT CSAIL, USA) 31:35
• (12) - William M. Wells III (Harvard Medical School and MIT CSAIL, USA) 45:50
• (13) - Alison Noble (University of Oxford, United Kingdom) 1:14:15
• (14) - Daniel Rueckert (Imperial College London, United Kingdom) 57:31
• (15) - Daniel Rueckert (Imperial College London, United Kingdom) 48:12
• (16) - Max Welling (University of Amsterdam, The Netherlands) 1:13:38
• (17) - Raquel Urtasun (University of Toronto, Canada) 55:07
• (18) - Ben Glocker (Imperial College London, United Kingdom) 59:57
• (19) - Andrea Vedaldi (University of Oxford, United Kingdom) 1:27:14
• (20) - Raquel Urtasun (University of Toronto, Canada) 1:01:30
• (21) - Andrea Vedaldi (University of Oxford, United Kingdom) 1:04:22
• (22) - Max Welling (University of Amsterdam, The Netherlands) 1:12:43
• (23) - Menarini 2:30

MEC 2015 Winners

ID#4 - DWI and Microstructure

Maxime Taquet
1st Prize Expert Panel.

ID#5 - Epipolar Consistency of X-ray Images

Andre Aichert
1st Prize Popular Vote.

ID#3 - Random walks in medical image processing

Mattias Heinrich
2nd Prize Expert Panel.

ID#2 - Understanding an MRI Pulse Sequence using a Guitar

Dr. Battista
Medical Biophysics as Western University
2nd Prize Popular Vote.

MISS 2014 Talks

• (01) - Mike Brady (University of Oxford, UK) 1:12:58
• (02) - Polina Golland (Massachusetts Institute of Technology, US) 49:30
• (03) - Polina Golland (Massachusetts Institute of Technology, US) 41:56
• (04) - Nikos Paragios (Ecole Centrale Paris, France) 51:31
• (05) - Xavier Pennec (INRIA, France) 1:00:34
• (06) - Nikos Paragios (Ecole Centrale Paris, France) 53:49
• (06 Pt02) - Nikos Paragios (Ecole Centrale Paris, France) 25:57
• (07) - Guido Gerig (University of Utah, US) 1:00:41
• (08) - Xavier Pennec (INRIA, France) 1:05:03
• (09) - Guido Gerig (University of Utah, US) 53:00
• (10) - Herve Delingette (INRIA, France) 1:39:04
• (11) - Antonio Criminisi (Microsoft Research, Cambridge, UK) 59:01
• (12) - Antonio Criminisi (Microsoft Research, Cambridge, UK) 50:15
• (14) - Nassir Navab (Technical University of Munich, Germany) 1:12:57
• (13) - Tim Salcudean (University of British Columbia, CA) 48:00
• (15) - Tim Salcudean (University of British Columbia, CA) 47:18
• (16) - Nassir Navab (Technical University of Munich, Germany) 48:08
• (17) - Mike Brady (University of Oxford, UK) 1:10:51
• Miss 2014 - Medical imaging summer school

MEC 2014 Winners

ID3: Your friendly guide to human brain atlases.

1^st place Expert Panel
Yiming Xiao and Ian Gerard
Montreal Neurological Institute, McGill University

ID9 - Singular Value Decomposition

2^nd place Expert Panel
Xiao Huang, Xiao Xue, Judith Zimmermann, Piotr Wojewnik
Technical University Munich

ID13 - Statistics on Lie groups for Computational Anatomy

1^st place Popular Vote
Nina Miolane, Bishesh Khanal
INRIA Sophia Antipolis

ID11 - Intraoperative Nuclear Imaging

2^nd place Popular Vote
Asli Okur, Philipp Matthies, Jose Gardiazabal, Oliver Zettinig, Christoph Hennersperger, Richard Brosig, Nassir Navab
Technical University Munich, Johns Hopkins

MEC 2014 & 2015 Entries in Random Order

The entire MEC2014 playlist is available here.

ID#1 - Automatic Segmentation of Interacting Cells

Danna Gurari

ID#6 - Going with the Flow - How 3D Printing and Prototype Design can Fight Coronary Artery Disease.

Susann Beier

ID1 - Motion Artifacts in Computed Tomography

Jerry Battista, Colin Versnick, and Kevin Jordan
Western University

ID2 - 3DMeshMetric video tutorial

Juliette Pera, Francois Budin, Tung Nguyen, Beatriz Paniagua
UNC-Chapel Hill

ID4 - Manopt, a Matlab toolbox for optimization on matrix manifolds

Nicolas Boumal
Universite catholique de Louvain

ID5 - Sparsity-Based Regularization

Shadi Albarqouni
Technical University Munich

ID6 - Medical Augmented Reality

Severine Habert and Meng Ma
Technical University Munich

ID7 - Mutual Information

Andrii Kravtsiv, Burcu Altinkaya, Jun Shen, Yuxiang Gong, Zhengyu Shan
Technical University Munich

ID8 - Ray Casting

Laura Flores Sanchez, Jihye Jang, Nicola Leucht, Tushar Upadhyah, Tao Ye
Technical University Munich

ID10 - 5: 3D Craniofacial Quantification of Changes-Compute the Surface Distances using a Color Map

Nicole Pentis, Lucia Cevidanes, Antonio Ruellas, Vinicius Boen, Beatriz Paniagua, Francois Budin, Alexis Girault, Martin Styner, Steve Pieper
University of Michigan, University of North Carolina at Chapel Hill, Isomics Inc.

ID12 - Discrete Optimisation for Medical Image Registration

Mattias P. Heinrich
University of Lubeck, University of Oxford · More Info

ID14 - Medical Image Segmentation [2 parts]

Ramesh Sridharan
MIT CSAIL · More Info and both parts

ID15 - Continuous Spatio-Temporal Atlases of the Asymptomatic and Infarcted Hearts

Pau Medrano-Gracia
University of Auckland