Publications de Jiancheng Yang

Frenet-Serret Frame-based Decomposition for Part Segmentation of 3D Curvilinear Structures

Accurate segmentation of anatomical substructures within 3D curvilinear structures in medical imaging remains challenging due to their complex geometry and the scarcity of diverse, large-scale datasets for algorithm development and evaluation. In this pape ...

2025

A multimodal visual–language foundation model for computational ophthalmology

Jiancheng Yang

Springer Science and Business Media LLC2025

Tuning vision foundation models for rectal cancer segmentation from CT scans

Jiancheng Yang

Background Rectal cancer segmentation in CT is crucial for timely diagnosis. Despite promising methods, challenges remain due to the rectum’s complex anatomy and the lack of a comprehensive annotated dataset. Methods A total of 33,024 slice pairs from 398 ...

Springer Science and Business Media LLC2025

SimTA++: Simple attention neural network for clinical asynchronous time series

Jiancheng Yang

Elsevier BV2025

Efficient anatomical labeling of pulmonary tree structures via deep point-graph representation-based implicit fields

Pascal Fua, Jiancheng Yang

Pulmonary diseases rank prominently among the principal causes of death worldwide. Curing them will require, among other things, a better understanding of the complex 3D tree-shaped structures within the pulmonary system, such as airways, arteries, and vei ...

2025

Fundus2Video: Cross-Modal Angiography Video Generation from Static Fundus Photography with Clinical Knowledge Guidance

Jiancheng Yang

Fundus Fluorescein Angiography (FFA) is a critical tool for assessing retinal vascular dynamics and aiding in the diagnosis of eye diseases. However, its invasive nature and less accessibility compared to Color Fundus (CF) images pose significant challenge ...

Springer Nature2024

SGDA: Towards 3-D Universal Pulmonary Nodule Detection via Slice Grouped Domain Attention

Jiancheng Yang

Lung cancer is the leading cause of cancer death worldwide. The best solution for lung cancer is to diagnose the pulmonary nodules in the early stage, which is usually accomplished with the aid of thoracic computed tomography (CT). As deep learning thrives ...

IEEE COMPUTER SOC2024

Multi-task learning for medical foundation models

Jiancheng Yang

To address the challenge of pretraining foundational models with large datasets, a multi-task approach is proposed, thus helping to overcome the data scarcity problem in biomedical imaging. ...

SPRINGERNATURE2024

RibSeg v2: A Large-Scale Benchmark for Rib Labeling and Anatomical Centerline Extraction

Jiancheng Yang, Jason Ken Adhinarta, Ming Li

Automatic rib labeling and anatomical centerline extraction are common prerequisites for various clinical applications. Prior studies either use in-house datasets that are inaccessible to communities, or focus on rib segmentation that neglects the clinical ...

Institute of Electrical and Electronics Engineers2024

Advancing EGFR mutation subtypes prediction in NSCLC by combining 3D pretrained ConvNeXt, radiomics, and clinical features

Jiancheng Yang

Purpose The aim of this study was to develop a novel approach for predicting the expression status of Epidermal Growth Factor Receptor (EGFR) and its subtypes in patients with Non-Small Cell Lung Cancer (NSCLC) using a Three-Dimensional Convolutional Neura ...

FRONTIERS MEDIA SA2024