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Jiancheng Yang

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Related publications (36)

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

Xinchao Wang, Hua Sun, Li Zhang, Jiancheng Yang

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

Bo Du, Jiancheng Yang, 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

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

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

Bo Du, Li Zhang, Zhigang Li, Jiancheng Yang

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

Boyu Zhang, Jiancheng Yang, Ying Zhu, Yi Wu

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, Pamuditha Udaranga Wickramasinghe, Jiancheng Yang, 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

LSSANet: A Long Short Slice-Aware Network for Pulmonary Nodule Detection

Bo Du, Jiancheng Yang, Rui Xu

Convolutional neural networks (CNNs) have been demonstrated to be highly effective in the field of pulmonary nodule detection. However, existing CNN based pulmonary nodule detection methods lack the ability to capture long-range dependencies, which is vita ...

SPRINGER INTERNATIONAL PUBLISHING AG2022

What Makes for Automatic Reconstruction of Pulmonary Segments

Bo Du, Li Zhang, Hongwei Li, Jiancheng Yang, Jingyu Li

3D reconstruction of pulmonary segments plays an important role in surgical treatment planning of lung cancer, which facilitates preservation of pulmonary function and helps ensure low recurrence rates. However, automatic reconstruction of pulmonary segmen ...

SPRINGER INTERNATIONAL PUBLISHING AG2022

Improving the efficiency of identifying malignant pulmonary nodules before surgery via a combination of artificial intelligence CT image recognition and serum autoantibodies

Yi Ding, Zhen Gao, Jiancheng Yang

ObjectiveTo construct a new pulmonary nodule diagnostic model with high diagnostic efficiency, non-invasive and simple to measure. MethodsThis study included 424 patients with radioactive pulmonary nodules who underwent preoperative 7-autoantibody (7-AAB) ...

SPRINGER2022

ImplicitAtlas: Learning Deformable Shape Templates in Medical Imaging

Pascal Fua, Pamuditha Udaranga Wickramasinghe, Jiancheng Yang

2022

Model of crop growth, water flow, and solute transport in layered soil

David Andrew Barry, Jiancheng Yang

Agro-ecohydrological models are essential for managing scarce water resources and ensuring crop productivity. Here, a one-dimensional agro-ecohydrological model, LAWSTAC, capable of simulating water and solute transport in layered soil coupled with crop gr ...

2019

Defining the role of common variation in the genomic and biological architecture of adult human height

Paul Jack Mc Laren, Murielle Bochud, Jiancheng Yang, Zhaoming Wang

Using genome-wide data from 253,288 individuals, we identified 697 variants at genome-wide significance that together explained one-fifth of the heritability for adult height. By testing different numbers of variants in independent studies, we show that th ...

Nature Publishing Group2014

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