Skip to content. | Skip to navigation

Personal tools

Sections

UMR 5672

logo de l'ENS de Lyon
logo du CNRS
You are here: Home / Seminars / Machine Learning and Signal Processing / Image decomposition in Fluorescence Microscopy: A posterior sampling based approach

Image decomposition in Fluorescence Microscopy: A posterior sampling based approach

Ashesh Ashesh (PHD Student, Human Technopole, Milano, Italy)
When Mar 18, 2025
from 01:00 to 02:00
Where M7 101
Attendees Ashesh Ashesh
Add event to calendar vCal
iCal

Ashesh Ashesh 

Title:  Image decomposition in Fluorescence Microscopy: A posterior sampling based approach

Abstract:  Fluorescence microscopy faces limitations due to the microscope’s optics, fluorophore chemistry, and photon exposure limits. This necessitates trade-offs in imaging speed, resolution, and depth. In my talk, I will discuss the two deep-learning-based computational multiplexing techniques [AKDS+23, AJ24], and their application [ACZ+25] which we developed during my PhD that enhanced the imaging of multiple cellular structures within a single fluorescent channel, allowing faster imaging and reduced photon exposure. Given a superimposed image (say containing Nucleus and Tubulin), my PhD research is to predict its constituent images separately. Our approach can sample diverse predictions from a trained posterior and is GPU-efficient. At last, I will end my talk with our ongoing work on creating an approach which can handle different levels of superposition
 
Refs
[ACZ+25] Ashesh, Florian Jug et al. Microsplit: Semantic unmixing of fluorescent microscopy data. bioRxiv, 2025.
 
[AJ24] Ashesh and Florian Jug. denoisplit: a method for joint microscopy image splitting and unsupervised denoising. ECCV 2024, 2024.
 
[AKDS+23] Ashesh, Alexander Krull, Moises Di Sante, Francesco Pasqualini, and Florian Jug. usplit: Image decomposition for fluorescence microscopy. In Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), pages 21219–21229, October 2023.
 
 

Website: https://ashesh-0.github.io/

In Room M7 101, 1st floor, Monod campus, ENSL.