Minisymposium: Deep Learning for Bioimage Analysis

COBA/BINA Image Informatics/Boston BIAS

Join us at this minisymposium to discuss the current developments and future scope of DL in bioimage analysis

Broad Institute of MIT and Harvard, Merkin Building, Main Street, Cambridge, MA, USA

We are happy to announce that preceding the American Society for Cell Biology (ASCB) meeting, Broad Institute will be hosting a minisymposium on deep learning for bioimage analysis on Friday, Dec 1st. This event will bring in experts from multiple disciplines to share current advances in deep learning for bioimage analysis. The hybrid format of the meeting will allow everyone to have the flexibility to attend. 📅 Event Details:Date: Friday, December 1stTime: 9am - 3pmVenue: Broad Institute, Merkin Building, 415 Main St., Cambridge, MA 02142 / Virtually Special thanks to our sponsors, Bioimaging North America (BINA) and the Center for Open Bioimage Analysis (COBA). * Note: Please only register for the in-person event if you plan on attending in person at the Broad Institute. If you want to attend virtually or are unsure, please register for the virtual event.

Please see Zoom connection details below for remote attendance Please click the link below to join the webinar:https://broadinstitute.zoom.us/j/83698155727?pwd=1J9c-j2e19M-X8OdeS1r4O14oPODYg.Y_ADW3-84aFxhplHPasscode: 891221Or One tap mobile : +16468769923,,83698155727#,,,,*891221# US (New York) +16465588656,,83698155727#,,,,*891221# US (New York)Or Telephone: Dial(for higher quality, dial a number based on your current location): +1 646 876 9923 US (New York) +1 646 558 8656 US (New York)Webinar ID: 836 9815 5727Passcode: 891221 International numbers available: https://broadinstitute.zoom.us/u/kc1BJ9rVdU

Agenda

Welcome

 Data Driven Microscopy of the Tumor Microenvironment

Image analysis from the perspective of the 3D cell surface

On Current and Future Bioimage Analysis Challenges

Q&A - Kevin Eliceiri, Meghan Driscoll, Florian Jug

Insights from images: Cell Painting to accelerate drug discovery

Visual interpretability of deep learning models in cell imaging

Deep learning based tools for improved analysis of microscopy datasets

Q&A - Anne Carpenter, Assaf Zaritsky, Uri Manor

Unsupervised representation learning of chromatin images identifies changes in cell state and tissue organization and enables prediction of protein localization

Unsupervised representation learning of chromatin images  (full title in desc)

A framework for invariant rep. learning of complex intracellular structures

Self-supervised DL encodes high-res features of protein subcellular location

Q&A - Xinyi Zhang, Ritvik Vasan, Loic Royer

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Minisymposium: Deep Learning for Bioimage Analysis

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Minisymposium: Deep Learning for Bioimage Analysis

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