most citedShifting to Machine Supervision: Annotation-Efficient Semi and Self-Supervised Learning for Automatic Medical Image Segmentation and Classification

22 citations · 25 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2024

Exploring Intrinsic Properties of Medical Images for Self-Supervised Binary Semantic Segmentation

Pranav Singh, Jacopo Cirrone

Recent advancements in self-supervised learning have unlocked the potential to harness unlabeled data for auxiliary tasks, facilitating the learning of beneficial priors. This has…

cs.CV2024★ 1 cited

Free Form Medical Visual Question Answering in Radiology

Abhishek Narayanan, Rushabh Musthyala, Rahul Sankar +3

Visual Question Answering (VQA) in the medical domain presents a unique, interdisciplinary challenge, combining fields such as Computer Vision, Natural Language Processing, and Kno…

cs.CV2023★ 22 cited

Shifting to Machine Supervision: Annotation-Efficient Semi and Self-Supervised Learning for Automatic Medical Image Segmentation and Classification

Pranav Singh, Raviteja Chukkapalli, Shravan Chaudhari +5

Advancements in clinical treatment are increasingly constrained by the limitations of supervised learning techniques, which depend heavily on large volumes of annotated data. The a…

eess.IV2023★ 1 cited

Enhancing Medical Image Segmentation: Optimizing Cross-Entropy Weights and Post-Processing with Autoencoders

Pranav Singh, Luoyao Chen, Mei Chen +4

The task of medical image segmentation presents unique challenges, necessitating both localized and holistic semantic understanding to accurately delineate areas of interest, such…

cs.LG2023★ 1 cited

Efficient Representation Learning for Healthcare with Cross-Architectural Self-Supervision

Pranav Singh, Jacopo Cirrone

In healthcare and biomedical applications, extreme computational requirements pose a significant barrier to adopting representation learning. Representation learning can enhance th…