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

452 citations · 794 across the 41 of their papers we have counts for

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Showing 2023Show all

10 papers · 1 filter

eess.IV202320 cited

Long-term Dependency for 3D Reconstruction of Freehand Ultrasound Without External Tracker

Qi Li, Ziyi Shen, Qian Li +5

Objective: Reconstructing freehand ultrasound in 3D without any external tracker has been a long-standing challenge in ultrasound-assisted procedures. We aim to define new ways of…

cs.CV2023

Boundary-RL: Reinforcement Learning for Weakly-Supervised Prostate Segmentation in TRUS Images

Weixi Yi, Vasilis Stavrinides, Zachary M. C. Baum +5

We propose Boundary-RL, a novel weakly supervised segmentation method that utilises only patch-level labels for training. We envision the segmentation as a boundary detection probl…

cs.CV20231 cited

Privileged Anatomical and Protocol Discrimination in Trackerless 3D Ultrasound Reconstruction

Qi Li, Ziyi Shen, Qian Li +5

Three-dimensional (3D) freehand ultrasound (US) reconstruction without using any additional external tracking device has seen recent advances with deep neural networks (DNNs). In t…

eess.IV2023

A Recycling Training Strategy for Medical Image Segmentation with Diffusion Denoising Models

Yunguan Fu, Yiwen Li, Shaheer U Saeed +2

Denoising diffusion models have found applications in image segmentation by generating segmented masks conditioned on images. Existing studies predominantly focus on adjusting mode…

eess.IV2023

Interpolation-Split: a data-centric deep learning approach with big interpolated data to boost airway segmentation performance

Wing Keung Cheung, Ashkan Pakzad, Nesrin Mogulkoc +14

The morphology and distribution of airway tree abnormalities enables diagnosis and disease characterisation across a variety of chronic respiratory conditions. In this regard, airw…

eess.IV2023

Combiner and HyperCombiner Networks: Rules to Combine Multimodality MR Images for Prostate Cancer Localisation

Wen Yan, Bernard Chiu, Ziyi Shen +8

One of the distinct characteristics in radiologists' reading of multiparametric prostate MR scans, using reporting systems such as PI-RADS v2.1, is to score individual types of MR…