activity
20172026
most citedMONAI: An open-source framework for deep learning in healthcare

452 citations · 797 across the 42 of their papers we have counts for

collaborators
Showing 2024Show all

9 papers · 1 filter

cs.CV2024

Segmentation by registration-enabled SAM prompt engineering using five reference images

Yaxi Chen, Aleksandra Ivanova, Shaheer U. Saeed +4

The recently proposed Segment Anything Model (SAM) is a general tool for image segmentation, but it requires additional adaptation and careful fine-tuning for medical image segment…

eess.IV20243 cited

Nonrigid Reconstruction of Freehand Ultrasound without a Tracker

Qi Li, Ziyi Shen, Qianye Yang +4

Reconstructing 2D freehand Ultrasound (US) frames into 3D space without using a tracker has recently seen advances with deep learning. Predicting good frame-to-frame rigid transfor…

cs.CV2024

Biomechanics-informed Non-rigid Medical Image Registration and its Inverse Material Property Estimation with Linear and Nonlinear Elasticity

Zhe Min, Zachary M. C. Baum, Shaheer U. Saeed +4

This paper investigates both biomechanical-constrained non-rigid medical image registrations and accurate identifications of material properties for soft tissues, using physics-inf…

eess.IV20241 cited

Poisson Ordinal Network for Gleason Group Estimation Using Bi-Parametric MRI

Yinsong Xu, Yipei Wang, Ziyi Shen +7

The Gleason groups serve as the primary histological grading system for prostate cancer, providing crucial insights into the cancer's potential for growth and metastasis. In clinic…

cs.CV2024

Competing for pixels: a self-play algorithm for weakly-supervised segmentation

Shaheer U. Saeed, Shiqi Huang, João Ramalhinho +8

Weakly-supervised segmentation (WSS) methods, reliant on image-level labels indicating object presence, lack explicit correspondence between labels and regions of interest (ROIs),…

cs.CV2024

One registration is worth two segmentations

Shiqi Huang, Tingfa Xu, Ziyi Shen +4

The goal of image registration is to establish spatial correspondence between two or more images, traditionally through dense displacement fields (DDFs) or parametric transformatio…