The McMedHacks program consists of 8 weeks of presentations and interactive workshops that will help you learn the fundamentals of medical image analysis and deep learning in Python. Each week will have one presentation session and one workshop.

During the presentations sessions leaders in industry and researchers with cutting edge medical image analysis and deep learning projects will present their work. The purpose of these presentation sessions is to motivate and inspire you for the upcoming workshop.

The interactive workshops will be tutorials and demonstrations of how to apply deep learning based analysis to various medical imaging modalities. Participants can follow along and modify the code during the workshops using Google Colab.

The workshops will take place from June 12th until July 31st. After the workshops we will be hosting the McMedHacks hackathon as an opportunity to practice your skills in a friendly competition. More information about the hackathon is coming soon.


Week 1 – Intro to Python for deep learning

Presentation June 12th 14:00-15:30 EDT

Opening ceremony: The Use of Artificial Intelligence in Radiotherapy
Speaker: Shirin Abbasinejad Enger, PhD

WorkshopJune 13th 10:00-11:30 EDT

Introduction to Python for deep learning
Instructors: Yujing Zou

Introduction to Python for deep learning
Instructors: Luca Weishaupt,

Introduction to Pytorch
Instructor: Hossein Jafarzadeh

Week 2 – Intro to deep learning

Presentation June 19th 10:00 -11:30 EDT

Visual Analytics for Cancer Radiotherapy
Speaker: Renata Raidou, PhD

The past, present, and future of machine learning in medical imaging and related applications
Speaker: Roy Keyes, PhD

WorkshopJune 20th 10:00-11:30 EDT

Introduction to deep learning
Instructor: Ximeng Mao

Week 3 – Histopathology and image analysis

Presentation June 25th 12:00-13:30 EDT

Limbus AI

Experiences in medical software entrepreneurship
Speaker: Karl Otto, PhD

Building and deploying AI models for clinical practice

Speaker: Joshua Giambatista, MD

Medical imaging machine learning pipelines for production

Speaker: Carter Kolbeck M.Sc.;

Shipping AI software in a regulated medical device industry

Speaker: Jonathan Giambatista, B.A. Sc.

WorkshopJune 27th 10:00-11:30 EDT

Digital Histopathological Image analysis
Instructor: Luca Weishaupt

Brief Intro to Histopathological Images
Instructor: Yujing Zou

Evaluation of machine learning models 
Instructor: Farhad Maleki, PhD

Week 4 – CT and semantic segmentation

Presentation July 3rd 10:00-11:30 EDT

Multi-modal Machine Learning for CT – From an example to Generality
Speaker: Christina Gillmann, PhD

Medical Imaging Analysis and Deep Learning Applications in Brachytherapy
Speaker: Christopher Deufel, PhD

WorkshopJuly 4th 10:00-11:30 EDT
3D image augmentation and its use case in semantic segmentation
Instructor: Farhad Maleki, PhD

Week 5 – Ultrasound and instance segmentation

Presentation July 10th 10:00-11:30 EDT

Artificial Intelligence in Medical Imaging: Image-based biomarkers & beyond

Speaker: Reza Forghani, PhD

WorkshopJuly 11th 10:00-11:30 EDT
Ultrasound and instance segmentation
Instructors: Peter Watson, PhD, Yujing Zou, Luca Weishaupt

Week 6 – MR and GAN-based segmentation

Presentation July 16th 10:00-11:30 EDT

Academia to industry and the role AI has played in both
Speaker: Andre Diamant, PhD

MEDomics: integrative data modelling in oncology
Speaker: Martin Vallières, PhD

A Machine Learning Radiation Therapy System from Bench to Bedside
Speaker: Professor Chris McIntosh

WorkshopJuly 18th 10:00-11:30 EDT
MR and GAN-based segmentation
Instructors: Yiping Wang

Week 7 – Multimodality and outcome prediction

Presentation July 24th 10:00-11:30 EDT

Medical Imaging in the age of AI
Speaker: Lei Xing, PhD

Data mining in radiotherapy: understanding the link between dose and long-term side effects
Speaker: Marianne Aznar, PhD

Delivering value in healthcare with AI
Speaker: Mark Gooding, PhD

WorkshopJuly 28th 19:00-20:30 EDT
Multimodality and outcome prediction
Instructor: Ibrahim Chamseddine, PhD

Week 8 – Closing ceremony

Presentation July 31st 10:00-12:15 EDT

Conditional Generation of Medical Images via Disentangled Adversarial Inference
Speaker: Mohammad Havaei, PhD

A Weakly Supervised Consistency-based Learning Method for COVID-19 Segmentation in CT Images
Speaker: Issam Laradji, PhD

Distributed Deep Learning Techniques for Medical Imaging
Speaker: Ken Chang, PhD

Future directions in machine learning and their application in healthcare
Speaker: Issam El Naqa, PhD

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