Description

The school goal is to inform the community about exciting opportunities at the interface of biomedical signal processing and modern problems in clinical medicine. Drawing on the experience of lecturers who research at this interface, we hope to give a tutorial overview of problems involving the analysis and integration of multi-modal signals for clinical use.

Our lecturers will address the following themes around biomedical signal integration, spread over 6 weeks, with one theme per week. Each week’s theme will involve one 1.5 hr lecture on the topic. The overall outline of themes are around the following areas:

  1. Introduction to Multimodal Data Integration in Biomedical Sciences (examples from healthcare).
  2. Brief Introduction to 1D/2D/3D and higher-dimensional signals in Biomedicine
  3. Review of Signal Processing techniques for Biomedical Signals (representation, prediction/inference)
  4. Predictive modeling, including AI/ML, leveraging ideas from signal analysis under biomedical constraints, (eg: structured sparsity, multimodal sensors for smart health etc)
  5. Case studies from Oncology Bioinformatics, NeuroImaging, Computational Medicine (motivating examples from various domains will be used in the explanation of the previous topics)

Logistics

  • To be held in January-February 2022, one theme per week.
  • The school will be totally virtual, with pre-recorded videos of each lecture, to enable access to students from all time zones.
  • An office hour will be scheduled for live discussion with each lecturer, using Zoom or similar platform.
  • The Classroom platform will be used to manage the course, with videos and complementary material, consultations and discussions.
  • Participation certificate: to get approval from the school, a short test must be answered for each lecture, with a minimum of 50% of correct answers on average.

Registration

  • No registration fee is required.
  • Registration must be performed by completing the Registration Form with all the required information.
  • The institutional email address and a gmail address (for google classroom) are required.


Sponsoring Institution

IEEE Signal Processing Society (IEEE SPS)

Organizers

SPS BISP Technical Committee, Education Subcommittee:

  • Dr. Arvind Rao, IEEE Senior Member & Associate Professor, Departments of Computational Medicine & Bioinformatics, Biomedical Engineering and Biostatistics, University of Michigan Ann Arbor, USA
  • Dr. Pamela Guevara, IEEE Member &  Associate Professor, Universidad de Concepción, Chile & Principal Investigator, Advanced Center for Electrical and Electronical Engineering (AC3E), Chile

Contact Information

If you have any questions, please contact us by email at mmbioschool2021@gmail.com.



Abstract Video competition

All school participants will be invited to participate in the school abstract competition.
They will have to upload a 3-minute video of their work in the area of biomedical image analysis.

The school organizing committee will select 6 abstracts.

At a closing session of the school, the selected works will be presented and the best works selected.

The following awards will be granted to the best abstracts:

  • Best abstract: 400 USD
  • Second place: 300 USD
  • An award of 300 USD will also be granted to the video with the highest number of votes from the students of the school, among all the submitted abstracts.


Speakers

Dr. Shaikh A. Fattah

Professor, Department of EEE, BUET, Bangladesh

Lecture title: “Multi-perspective Deep Learning Networks for Bio-signal Analysis” (Theme 4).
The lecture will cover both unimodal and multi-modal (multi-sensor) analysis.

Dr. Mathews Jacob

Department of Electrical and Computer Engineering, University of Iowa, Iowa City, USA

Director of Computational Biomedical Imaging Group (CBIG), University of Iowa, Iowa City, USA

Lecture title: “Signal processing algorithms for next-generation MRI”.

Dr. Baiying Lei

Department of Medical Information Engineering, Shenzhen University

Lecture title: “Multi-modal and Multi-time Neuroimaging Learning for Brain Disease Analysis”.

Dr. Shashikant Patil

Associate Professor and Head, Computer Science and Engineering (AI & ML)

Vishwaniketan Institute of Management Entrepreneurship Engineering and Technology Khalapur Raigad

Lecture Title: “Caries Detection using Image Processing Techniques”.

Dr. Tammy Riklin Raviv

Associate Professor, Electrical and Computer Engineering Department, Ben Gurion University

Lecture title: “Instance Segmentation of Live-Cell Microscopy Videos via Deep Learning”.

Dr. Celia Shahnaz

Professor, Department of EEE, BUET, Dhaka, Bangladesh

Lecture title: “Deep Learning Applications for Medical Image Analysis”.

Elisa Warner

University of Michigan Department of Computational Medicine and Bioinformatics

Lecture title: “Introduction to Multimodal Machine Learning (Parts I and II)”.