5 citations · 10 across the 15 of their papers we have counts for
7 papers · 1 filter
ART-ASyn: Anatomy-aware Realistic Texture-based Anomaly Synthesis Framework for Chest X-Rays
Qinyi Cao, Jianan Fan, Weidong Cai
Unsupervised anomaly detection aims to identify anomalies without pixel-level annotations. Synthetic anomaly-based methods exhibit a unique capacity to introduce controllable irreg…
SurgiATM: A Physics-Guided Plug-and-Play Model for Deep Learning-Based Smoke Removal in Laparoscopic Surgery
Mingyu Sheng, Jianan Fan, Dongnan Liu +3
During laparoscopic surgery, smoke generated by tissue cauterization can significantly degrade the visual quality of endoscopic frames, increasing the risk of surgical errors and h…
Gene-DML: Dual-Pathway Multi-Level Discrimination for Gene Expression Prediction from Histopathology Images
Yaxuan Song, Jianan Fan, Hang Chang +1
Accurately predicting gene expression from histopathology images offers a scalable and non-invasive approach to molecular profiling, with significant implications for precision med…
Towards Conditional Feature Alignment for Cross-Domain Counting
Zhuonan Liang, Dongnan Liu, Jianan Fan +6
Object counting models often degrade under cross-domain deployment because density composition varies across domains and is itself task-relevant. Standard feature alignment methods…
Sequential Spatial-Temporal Network for Interpretable Automatic Ultrasonic Assessment of Fetal Head during labor
Jie Gan, Zhuonan Liang, Jianan Fan +5
The intrapartum ultrasound guideline established by ISUOG highlights the Angle of Progression (AoP) and Head Symphysis Distance (HSD) as pivotal metrics for assessing fetal head de…
MIRROR: Multi-Modal Pathological Self-Supervised Representation Learning via Modality Alignment and Retention
Tianyi Wang, Jianan Fan, Dingxin Zhang +4
Histopathology and transcriptomics are fundamental modalities in oncology, encapsulating the morphological and molecular aspects of the disease. Multi-modal self-supervised learnin…
Medical Image Registration Meets Vision Foundation Model: Prototype Learning and Contour Awareness
Hao Xu, Tengfei Xue, Jianan Fan +7
Medical image registration is a fundamental task in medical image analysis, aiming to establish spatial correspondences between paired images. However, existing unsupervised deform…