Publications by 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

Ming Li, Jiancheng Yang, Jason Ken Adhinarta

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

Two-stage error detection to improve electron microscopy image mosaicking

Jiancheng Yang

Large-scale electron microscopy (EM) has enabled the reconstruction of brain connectomes at the synaptic level by serially scanning over massive areas of sample sections. The acquired big EM data sets raise the great challenge of image mosaicking at high a ...

2024

Multimodal fusion of liquid biopsy and CT enhances differential diagnosis of early-stage lung adenocarcinoma

Jun Lu, Hua Zhong, Li Zhang, Yunhua Zhang, Jiancheng Yang

This research explores the potential of multimodal fusion for the differential diagnosis of early-stage lung adenocarcinoma (LUAD) (tumor sizes < 2 cm). It combines liquid biopsy biomarkers, specifically extracellular vesicle long RNA (evlRNA) and the comp ...

Nature Portfolio2024

MedShapeNet - a large-scale dataset of 3D medical shapes for computer vision

Pascal Fua, Jiancheng Yang

The shape is commonly used to describe the objects. State-of-the-art algorithms in medical imaging are predominantly diverging from computer vision, where voxel grids, meshes, point clouds, and implicit surface models are used. This is seen from the growin ...

2024

BigNeuron: a resource to benchmark and predict performance of algorithms for automated tracing of neurons in light microscopy datasets

Pascal Fua, Sean Lewis Hill, Amos Sironi, Jiancheng Yang, Jian Zhou, Siqi Liu, Xiang Li, Jie Zhou

BigNeuron is an open community bench-testing platform with the goal of setting open standards for accurate and fast automatic neuron tracing. We gathered a diverse set of image volumes across several species that is representative of the data obtained in m ...

2023

Robust Outlier Rejection for 3D Registration with Variational Bayes

Mathieu Salzmann, Zheng Dang, Zhen Wei, Jiancheng Yang, Haobo Jiang

Learning-based outlier (mismatched correspondence) rejection for robust 3D registration generally formulates the outlier removal as an inlier/outlier classification problem. The core for this to be successful is to learn the discriminative inlier/outlier f ...

Ieee Computer Soc2023

Center-Based Decoupled Point Cloud Registration for 6D Object Pose Estimation

Mathieu Salzmann, Zheng Dang, Jiancheng Yang, Haobo Jiang

In this paper, we propose a novel center-based decoupled point cloud registration framework for robust 6D object pose estimation in real-world scenarios. Our method decouples the translation from the entire transformation by predicting the object center an ...

Ieee Computer Soc2023

MixCycle: Mixup Assisted Semi-Supervised 3D Single Object Tracking with Cycle Consistency

Mathieu Salzmann, Kun Sun, Yunhua Zhang, Jiancheng Yang

3D single object tracking (SOT) is an indispensable part of automated driving. Existing approaches rely heavily on large, densely labeled datasets. However, annotating point clouds is both costly and time-consuming. Inspired by the great success of cycle t ...

Ieee Computer Soc2023

Invasiveness assessment by artificial intelligence against intraoperative frozen section for pulmonary nodules

Jiancheng Yang

PurposeTo investigate the performance of an artificial intelligence (AI) algorithm for assessing the malignancy and invasiveness of pulmonary nodules in a multicenter cohort.MethodsA previously developed deep learning system based on a 3D convolutional neu ...

2023

Prognostic impact of deep learning-based quantification in clinical stage 0-I lung adenocarcinoma

Qiong Li, Li Zhang, Lin Chen, Jiancheng Yang, Ying Zhu

Objectives To evaluate the performance of automatic deep learning (DL) algorithm for size, mass, and volume measurements in predicting prognosis of lung adenocarcinoma (LUAD) and compared with manual measurements. ...

SPRINGER2023

China lung cancer screening (CLUS) version 2.0 with new techniques implemented: Artificial intelligence, circulating molecular biomarkers and autofluorescence bronchoscopy

Jiancheng Yang

Objective: The present study, CLUS version 2.0, was conducted to evaluate the performance of new techniques in improving the implementation of lung cancer screening and to validate the efficacy of LDCT in reducing lung cancer-specific mortality in a high-r ...

ELSEVIER IRELAND LTD2023