7 citations · 15 across the 9 of their papers we have counts for
16 papers
A Domain-specific Perceptual Metric via Contrastive Self-supervised Representation: Applications on Natural and Medical Images
Hongwei Bran Li, Chinmay Prabhakar, Suprosanna Shit +7
Quantifying the perceptual similarity of two images is a long-standing problem in low-level computer vision. The natural image domain commonly relies on supervised learning, e.g.,…
Topologically faithful image segmentation via induced matching of persistence barcodes
Nico Stucki, Johannes C. Paetzold, Suprosanna Shit +2
Image segmentation is a largely researched field where neural networks find vast applications in many facets of technology. Some of the most popular approaches to train segmentatio…
Relationformer: A Unified Framework for Image-to-Graph Generation
Suprosanna Shit, Rajat Koner, Bastian Wittmann +8
A comprehensive representation of an image requires understanding objects and their mutual relationship, especially in image-to-graph generation, e.g., road network extraction, blo…
A unified 3D framework for Organs at Risk Localization and Segmentation for Radiation Therapy Planning
Fernando Navarro, Guido Sasahara, Suprosanna Shit +4
Automatic localization and segmentation of organs-at-risk (OAR) in CT are essential pre-processing steps in medical image analysis tasks, such as radiation therapy planning. For in…
Partial supervision for the FeTA challenge 2021
Lucas Fidon, Michael Aertsen, Suprosanna Shit +4
This paper describes our method for our participation in the FeTA challenge2021 (team name: TRABIT). The performance of convolutional neural networks for medical image segmentation…
Semi-Implicit Neural Solver for Time-dependent Partial Differential Equations
Suprosanna Shit, Ivan Ezhov, Leon Mächler +6
Fast and accurate solutions of time-dependent partial differential equations (PDEs) are of pivotal interest to many research fields, including physics, engineering, and biology. Ge…