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Jiancheng Yang

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Publications associées (36)

Deep learning-based solid component measuring enabled interpretable prediction of tumor invasiveness for lung adenocarcinoma

Jiancheng Yang, Li Zhang, Xinchao Wang, Hua Sun

Background: The nature of the solid component of subsolid nodules (SSNs) can indicate tumor pathological invasiveness. However, preoperative solid component assessment still lacks a reference standard.Methods: In this retrospective study, an AI algorithm w ...

Elsevier Ireland Ltd2023

MULTI-TASK CURRICULUM LEARNING FOR PARTIALLY LABELED DATA

Jiancheng Yang, Stanislav Lukyanenko

Incomplete labels are common in multi-task learning for biomedical applications due to several practical difficulties, e.g., expensive annotation efforts by experts, limit of data collection, different sources of data. A naive approach to enable joint lear ...

IEEE2023

Efficient Lung Nodule Detection via 3D Deep Learning with Shifted Convolutions

Jiancheng Yang, Bo Du, Kang Yuan

The high computational costs of deep convolutional neural networks hinder their deployment in real-world applications, including pulmonary nodule detection from CT scans where large 3D image sizes amplify the issue. This paper presents a novel 3D method to ...

IEEE2023

One-shot Retinal Artery and Vein Segmentation via Cross-modality Pretraining

Jiancheng Yang

Purpose: To perform one-shot retinal artery and vein segmentation with cross-modality artery-vein (AV) soft -label pretraining.Design: Cross-sectional study.Subjects: The study included 6479 color fundus photography (CFP) and arterial-venous fundus fluores ...

Elsevier2023

Deep learning parametric response mapping from inspiratory chest CT scans: a new approach for small airway disease screening

Jiancheng Yang, Zhiye Wang, Jun Lu, Zhigang Li, Lin Qi, Ming Li, Bo Du, Yuxuan Sun, Ziyi Liu

Objectives Parametric response mapping (PRM) enables the evaluation of small airway disease (SAD) at the voxel level, but requires both inspiratory and expiratory chest CT scans. We hypothesize that deep learning PRM from inspiratory chest CT scans can eff ...

BMC2023

Deep learning predicts malignancy and metastasis of solid pulmonary nodules from CT scans

Jiancheng Yang

In the clinic, it is difficult to distinguish the malignancy and aggressiveness of solid pulmonary nodules (PNs). Incorrect assessments may lead to delayed diagnosis and an increased risk of complications. We developed and validated a deep learning-based m ...

FRONTIERS MEDIA SA2023

Scale-Aware Test-Time Click Adaptation for Pulmonary Nodule and Mass Segmentation

Jiancheng Yang, Li Zhang, Zhigang Li, Bo Du

Pulmonary nodules and masses are crucial imaging features in lung cancer screening that require careful management in clinical diagnosis. Despite the success of deep learning-based medical image segmentation, the robust performance on various sizes of lesi ...

Springer International Publishing Ag2023

Multi-site, Multi-domain Airway Tree Modeling

Jiancheng Yang, Yi Wu, Ying Zhu, Boyu Zhang

Open international challenges are becoming the de facto standard for assessing computer vision and image analysis algorithms. In recent years, new methods have extended the reach of pulmonary airway segmentation that is closer to the limit of image resolut ...

Elsevier2023

Topology Repairing of Disconnected Pulmonary Airways and Vessels: Baselines and a Dataset

Jiancheng Yang

Accurate segmentation of pulmonary airways and vessels is crucial for the diagnosis and treatment of pulmonary diseases. However, current deep learning approaches suffer from disconnectivity issues that hinder their clinical usefulness. To address this cha ...

Springer International Publishing Ag2023

Neural Annotation Refinement: Development of a New 3D Dataset for Adrenal Gland Analysis

Pascal Fua, Jiancheng Yang, Pamuditha Udaranga Wickramasinghe, Rui Shi

The human annotations are imperfect, especially when produced by junior practitioners. Multi-expert consensus is usually regarded as golden standard, while this annotation protocol is too expensive to implement in many real-world projects. In this study, w ...

SPRINGER INTERNATIONAL PUBLISHING AG2022

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MULTI-TASK CURRICULUM LEARNING FOR PARTIALLY LABELED DATA

Jiancheng Yang, Stanislav Lukyanenko

IEEE2023

Efficient Lung Nodule Detection via 3D Deep Learning with Shifted Convolutions

Jiancheng Yang, Bo Du, Kang Yuan

IEEE2023

Deep learning parametric response mapping from inspiratory chest CT scans: a new approach for small airway disease screening

Jiancheng Yang, Zhiye Wang, Jun Lu, Zhigang Li, Lin Qi, Ming Li, Bo Du, Yuxuan Sun, Ziyi Liu

BMC2023

Topology Repairing of Disconnected Pulmonary Airways and Vessels: Baselines and a Dataset

Jiancheng Yang

Springer International Publishing Ag2023

Deep learning-based solid component measuring enabled interpretable prediction of tumor invasiveness for lung adenocarcinoma

Jiancheng Yang, Li Zhang, Xinchao Wang, Hua Sun

Elsevier Ireland Ltd2023