Oindrila Haldar

2026

1. ISBI 26

   Visualization Guided Retinal Fluid Segmentation of Optical Coherence Tomography B-Scans

   S. Mandal, O. Haldar, C. S. Seelamantula, and R. Prasad

   In 2026 IEEE 23rd International Symposium on Biomedical Imaging (ISBI), Apr 2026

   Abstract DOI Download .bib

   @inproceedings{11515864, author = {Mandal, S. and Haldar, O. and Seelamantula, C. S. and Prasad, R.}, booktitle = {2026 IEEE 23rd International Symposium on Biomedical Imaging (ISBI)}, title = {Visualization Guided Retinal Fluid Segmentation of Optical Coherence Tomography B-Scans}, year = {2026}, pages = {1-4}, keywords = {Modeling;Dies;Fluids;Visualization;Pathology;Retina;Printing;Timing;Training;Imaging;Optical Coherence Tomography;Medical Image Segmentation;Class Activation Maps;CLAVIS}, doi = {10.1109/ISBI61048.2026.11515864}, issn = {1945-8452}, month = apr, }

   Vision loss remains a critical global health issue, with conditions such as diabetic macular edema and age-related macular degeneration often detected only after substantial retinal damage. Early retinal fluid accumulation is a key biomarker, and Optical Coherence Tomography (OCT) provides noninvasive, high-resolution retinal imaging essential for diagnosis. Accurate segmentation of retinal structures is crucial, yet recent conventional deep learning approaches often do not provide satisfactory performance because fluid regions occupy a small portion of the image, leading to inefficient computation and reduced accuracy. We propose CLAVIS, a novel plug-and-play pipeline that leverages CLAssification outputs to generate VIsualizations and guide Segmentation, generating more precise maps of the fluid regions. We leverage visualization techniques to target image regions that influenced the classification outcome. Experimental results demonstrate that this guidance strategy improves Dice score by $\mathbf{+ 0. 1 4}$ on the average and up to $\mathbf{+ 0. 1 8}$ for some pathologies.