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20182026
most citedAnalyzing Overfitting under Class Imbalance in Neural Networks for Image Segmentation

191 citations · 211 across the 15 of their papers we have counts for

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11 papers · 1 filter

cs.CV2026

LiFUSE: Frequency-Spatial Unified Self-Supervised Pretraining for Liver Disease Analysis on Non-contrast CT

Hao Zhang, Yi Huang, Wei Liu +6

Given the growing global burden of liver tumors and diffuse liver diseases, non-contrast computed tomography (NCCT) is increasingly used for opportunistic screening because of its…

cs.CV2026

CARD: Calibration via Agreement in Reverse Diffusion for Out-of-Domain MRI Segmentation

Jiaheng Dai, Weidong Guo, Qingbiao Li +4

Probability calibration aligns model confidence with predictive accuracy, enabling clinicians to identify unreliable segmentation regions. This alignment breaks down under domain s…

cs.CV2026

CIPHER: Causal Intervention Pathways for Healthcare Equity and Robustness

Xinyu Jia, Weidong Guo, Wangyuan Zhao +3

Deep learning models for medical diagnosis frequently exhibit substantial performance disparities across sensitive subgroups (e.g., race, sex), even when average accuracy is high.…

cs.CV2026

Enhancing Brain MRI Anomaly Detection and Reasoning with ROI Rethink and Synthetic Data

Shangkun Li, Jie Xu, Yi Guo +2

Medical vision-language models typically generate diagnoses through single-pass inference without indicating which image regions support their conclusions. This lack of spatial gro…

cs.CV2026

DepthPilot: From Controllability to Interpretability in Colonoscopy Video Generation

Junhu Fu, Ke Chen, Weidong Guo +9

Controllable medical video generation has achieved remarkable progress, but it still lacks interpretability, which requires the alignment of generated contents with physical priors…

cs.CV2026

EchoAgent: Towards Reliable Echocardiography Interpretation with "Eyes","Hands" and "Minds"

Qin Wang, Zhiqing He, Yu Liu +8

Reliable interpretation of echocardiography (Echo) is crucial for assessing cardiac function, which demands clinicians to synchronously orchestrate multiple capabilities, including…

cs.CV2026

Fine-Grained Action Segmentation for Renorrhaphy in Robot-Assisted Partial Nephrectomy

Jiaheng Dai, Huanrong Liu, Tailai Zhou +7

Fine-grained action segmentation during renorrhaphy in robot-assisted partial nephrectomy requires frame-level recognition of visually similar suturing gestures with variable durat…

cs.CV2025

VAP-Diffusion: Enriching Descriptions with MLLMs for Enhanced Medical Image Generation

Peng Huang, Junhu Fu, Bowen Guo +3

As the appearance of medical images is influenced by multiple underlying factors, generative models require rich attribute information beyond labels to produce realistic and divers…

cs.CV2023

Joint Optimization of Class-Specific Training- and Test-Time Data Augmentation in Segmentation

Zeju Li, Konstantinos Kamnitsas, Qi Dou +2

This paper presents an effective and general data augmentation framework for medical image segmentation. We adopt a computationally efficient and data-efficient gradient-based meta…

cs.CV2021★ 191 cited

Analyzing Overfitting under Class Imbalance in Neural Networks for Image Segmentation

Zeju Li, Konstantinos Kamnitsas, Ben Glocker

Class imbalance poses a challenge for developing unbiased, accurate predictive models. In particular, in image segmentation neural networks may overfit to the foreground samples fr…

cs.CV2018★ 3 cited

Left Ventricle Segmentation via Optical-Flow-Net from Short-axis Cine MRI: Preserving the Temporal Coherence of Cardiac Motion

Wenjun Yan, Yuanyuan Wang, Zeju Li +2

Quantitative assessment of left ventricle (LV) function from cine MRI has significant diagnostic and prognostic value for cardiovascular disease patients. The temporal movement of…