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20152025
most citedA large annotated medical image dataset for the development and evaluation of segmentation algorithms

718 citations · 1.8k across the 30 of their papers we have counts for

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13 papers · 1 filter

eess.IV2021

Lymph Node Detection in T2 MRI with Transformers

Tejas Sudharshan Mathai, Sungwon Lee, Daniel C. Elton +4

Identification of lymph nodes (LN) in T2 Magnetic Resonance Imaging (MRI) is an important step performed by radiologists during the assessment of lymphoproliferative diseases. The…

eess.IV20201 cited

One Click Lesion RECIST Measurement and Segmentation on CT Scans

Youbao Tang, Ke Yan, Jing Xiao +1

In clinical trials, one of the radiologists' routine work is to measure tumor sizes on medical images using the RECIST criteria (Response Evaluation Criteria In Solid Tumors). Howe…

eess.IV20206 cited

ENet: An Edge Enhanced Network for Accurate Liver and Tumor Segmentation on CT Scans

Youbao Tang, Yuxing Tang, Yingying Zhu +2

Developing an effective liver and liver tumor segmentation model from CT scans is very important for the success of liver cancer diagnosis, surgical planning and cancer treatment.…

eess.IV2020

Deep Small Bowel Segmentation with Cylindrical Topological Constraints

Seung Yeon Shin, Sungwon Lee, Daniel C. Elton +2

We present a novel method for small bowel segmentation where a cylindrical topological constraint based on persistent homology is applied. To address the touching issue which could…

eess.IV20204 cited

Cross-Domain Medical Image Translation by Shared Latent Gaussian Mixture Model

Yingying Zhu, Youbao Tang, Yuxing Tang +4

Current deep learning based segmentation models often generalize poorly between domains due to insufficient training data. In real-world clinical applications, cross-domain image a…

eess.IV20202 cited

Deep Network Interpolation for Accelerated Parallel MR Image Reconstruction

Chen Qin, Jo Schlemper, Kerstin Hammernik +3

We present a deep network interpolation strategy for accelerated parallel MR image reconstruction. In particular, we examine the network interpolation in parameter space between a…