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Sivan Biham is a Computer Vision Researcher and Algorithm Developer in Healthy.io. She works on healthcare-related products, taking them from the algorithm design stage to a fully implemented product with thousands of users worldwide. Sivan holds an M.Sc. in computer science from Weizmann Institute with a specialization in Computer Vision and Deep Learning and a B.Sc. in מןcomputer science and Neuroscience from Bar Ilan University. She is enthusiastic about using her algorithmic skills and knowledge to improve people’s health and life. As part of her daily work, Sivan emphasizes designing and implementing maintainable and modular algorithms with software architecture principles in mind. She always strives to play an integral role in the problem-solving process and others. In her spare time, she loves to run and practice yoga.
Sivan Biham is a Computer Vision Researcher and Algorithm Developer in Healthy.io. She works on healthcare-related products, taking them from the algorithm design stage to a fully implemented product with thousands of users worldwide. Sivan holds an M.Sc. in computer science from Weizmann Institute with a specialization in Computer Vision and Deep Learning and a B.Sc. in מןcomputer science and Neuroscience from Bar Ilan University. She is enthusiastic about using her algorithmic skills and knowledge to improve people’s health and life. As part of her daily work, Sivan emphasizes designing and implementing maintainable and modular algorithms with software architecture principles in mind. She always strives to play an integral role in the problem-solving process and others. In her spare time, she loves to run and practice yoga.
Measurement of changes to chronic wounds over time is the cornerstone for wound management and assessment. In this talk, Sivan will present a new framework that allows clinicians to visually track the healing progress over time. The presented framework artificially creates a consistent timeline from other visits of the same wound, where all views are shown at the same scale, location, and orientation. This framework receives as input a series of video scans and outputs a consistent timeline of 2D projected images. Sivan will describe how a combination of several computer vision algorithms, such as 3D modeling, deep learning, as well as classical algorithms, can be used to help clinicians visually monitor the wound healing process for the first time.
Measurement of changes to chronic wounds over time is the cornerstone for wound management and assessment. In this talk, Sivan will present a new framework that allows clinicians to visually track the healing progress over time. The presented framework artificially creates a consistent timeline from other visits of the same wound, where all views are shown at the same scale, location, and orientation. This framework receives as input a series of video scans and outputs a consistent timeline of 2D projected images. Sivan will describe how a combination of several computer vision algorithms, such as 3D modeling, deep learning, as well as classical algorithms, can be used to help clinicians visually monitor the wound healing process for the first time.
| 8:45 | Reception |
|---|---|
| 9:30 | Opening words by WiDS TLV ambassadors Or Basson and Noah Eyal Altman |
| 9:40 | Dr. Kira Radinski - Learning to predict the future of healthcare |
| 10:10 | Prof. Yonina Eldar - Model-Based Deep Learning: Applications to Imaging and Communications |
| 10:40 | Break |
| 10:50 | Lightning talks |
| 12:20 | Lunch & Poster session |
|---|---|
| 13:20 | Roundtable session & Poster session |
| 14:05 | Roundtable closure |
| 14:20 | Break |
| 14:30 | Dr. Anna Levant - 3D Metrology: Seeing the Unseen |
| 15:00 | Aviv Ben-Arie - Counterfactual Explanations: The Future of Explainable AI? |
| 15:30 | Closing remarks |
| 15:40 | End |
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