output
20192025
most citedThe Liver Tumor Segmentation Benchmark (LiTS)

1.2k citations

8 papers

astro-ph.IM2025★ 10 cited

Astronomical image denoising by self-supervised deep learning and restoration processes

Tie Liu, Yuhui Quan, Yingna Su +9

Image denoising based on deep learning has witnessed significant advancements in recent years. However, existing deep learning methods lack quantitative control of the deviation or…

cs.SD2024★ 6 cited

Multi-class Decoding of Attended Speaker Direction Using Electroencephalogram and Audio Spatial Spectrum

Yuanming Zhang, Jing Lu, Fei Chen +3

Decoding the directional focus of an attended speaker from listeners' electroencephalogram (EEG) signals is essential for developing brain-computer interfaces to improve the qualit…

cs.CV2024★ 43 cited

Deep learning-driven pulmonary artery and vein segmentation reveals demography-associated vasculature anatomical differences

Yuetan Chu, Gongning Luo, Longxi Zhou +13

Pulmonary artery-vein segmentation is crucial for disease diagnosis and surgical planning and is traditionally achieved by Computed Tomography Pulmonary Angiography (CTPA). However…

cs.AR2023★ 61 cited

Parallel in-memory wireless computing

Cong Wang, Gong-Jie Ruan, Zai-Zheng Yang +13

Parallel wireless digital communication with ultralow power consumption is critical for emerging edge technologies such as 5G and Internet of Things. However, the physical separati…

q-bio.BM2023★ 46 cited

Kainate receptor modulation by NETO2

Lingli He, Jiahui Sun, Yiwei Gao +10

Glutamate-gated kainate receptors (KARs) are ubiquitous in the central nervous system of vertebrates, mediate synaptic transmission on post-synapse, and modulate transmitter releas…

cs.CV2020★ 14 cited

AbdomenCT-1K: Is Abdominal Organ Segmentation A Solved Problem?

Jun Ma, Yao Zhang, Song Gu +14

With the unprecedented developments in deep learning, automatic segmentation of main abdominal organs seems to be a solved problem as state-of-the-art (SOTA) methods have achieved…

eess.IV2020★ 260 cited

Towards Data-Efficient Learning: A Benchmark for COVID-19 CT Lung and Infection Segmentation

Jun Ma, Yixin Wang, Xingle An +10

Purpose: Accurate segmentation of lung and infection in COVID-19 CT scans plays an important role in the quantitative management of patients. Most of the existing studies are based…

cs.CV2019★ 1.2k cited

The Liver Tumor Segmentation Benchmark (LiTS)

Patrick Bilic, Patrick Christ, Hongwei Bran Li +106

In this work, we report the set-up and results of the Liver Tumor Segmentation Benchmark (LiTS), which was organized in conjunction with the IEEE International Symposium on Biomedi…