4 citations · 7 across the 4 of their papers we have counts for
4 papers
SAM for Robust Mitochondria Instance Segmentation in Fluorescence Microscopy
Suyog Jadhav, Dilip K. Prasad, Krishna Agarwal
The morphological analysis of mitochondria in fluorescence microscopy (FM) is crucial for understanding cellular health, energy production, and metabolic regulation. While foundati…
MiShape: 3D Shape Modelling of Mitochondria in Microscopy
Abhinanda R. Punnakkal, Suyog S Jadhav, Alexander Horsch +2
Fluorescence microscopy is a quintessential tool for observing cells and understanding the underlying mechanisms of life-sustaining processes of all living organisms. The problem o…
Artefact removal in ground truth and noise model deficient sub-cellular nanoscopy images using auto-encoder deep learning
Suyog Jadhav, Sebastian Acuña, Krishna Agarwal +1
Image denoising or artefact removal using deep learning is possible in the availability of supervised training dataset acquired in real experiments or synthesized using known noise…
Multi-Plateau Ensemble for Endoscopic Artefact Segmentation and Detection
Suyog Jadhav, Udbhav Bamba, Arnav Chavan +2
Endoscopic artefact detection challenge consists of 1) Artefact detection, 2) Semantic segmentation, and 3) Out-of-sample generalisation. For Semantic segmentation task, we propose…