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most citedHunting imaging biomarkers in pulmonary fibrosis: Benchmarks of the AIIB23 challenge

26 citations · 53 across the 28 of their papers we have counts for

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13 papers · 1 filter

eess.IV2025

Shape-aware Sampling Matters in the Modeling of Multi-Class Tubular Structures

Minghui Zhang, Yaoyu Liu, Xin You +2

Accurate multi-class tubular modeling is critical for precise lesion localization and optimal treatment planning. Deep learning methods enable automated shape modeling by prioritiz…

eess.IV2025

Multi-Class Segmentation of Aortic Branches and Zones in Computed Tomography Angiography: The AortaSeg24 Challenge

Muhammad Imran, Jonathan R. Krebs, Vishal Balaji Sivaraman +60

Multi-class segmentation of the aorta in computed tomography angiography (CTA) scans is essential for diagnosing and planning complex endovascular treatments for patients with aort…

eess.IV2024

AirMorph: Topology-Preserving Deep Learning for Pulmonary Airway Analysis

Minghui Zhang, Chenyu Li, Fangfang Xie +8

Accurate anatomical labeling and analysis of the pulmonary structure and its surrounding anatomy from thoracic CT is getting increasingly important for understanding the etilogy of…

eess.IV2024

Topology-Aware Exploration of Circle of Willis for CTA and MRA: Segmentation, Detection, and Classification

Minghui Zhang, Xin You, Hanxiao Zhang +1

The Circle of Willis (CoW) vessels is critical to connecting major circulations of the brain. The topology of the vascular structure is clinical significance to evaluate the risk,…

eess.IV2024

SLoRD: Structural Low-Rank Descriptors for Shape Consistency in Vertebrae Segmentation

Xin You, Yixin Lou, Minghui Zhang +2

Automatic and precise multi-class vertebrae segmentation from CT images is crucial for various clinical applications. However, due to similar appearances between adjacent vertebrae…

eess.IV2023★ 26 cited

Hunting imaging biomarkers in pulmonary fibrosis: Benchmarks of the AIIB23 challenge

Yang Nan, Xiaodan Xing, Shiyi Wang +38

Airway-related quantitative imaging biomarkers are crucial for examination, diagnosis, and prognosis in pulmonary diseases. However, the manual delineation of airway trees remains…

eess.IV2023

Accurate Airway Tree Segmentation in CT Scans via Anatomy-aware Multi-class Segmentation and Topology-guided Iterative Learning

Puyang Wang, Dazhou Guo, Dandan Zheng +8

Intrathoracic airway segmentation in computed tomography (CT) is a prerequisite for various respiratory disease analyses such as chronic obstructive pulmonary disease (COPD), asthm…

eess.IV2023★ 2 cited

Multi-site, Multi-domain Airway Tree Modeling (ATM'22): A Public Benchmark for Pulmonary Airway Segmentation

Minghui Zhang, Yangqian Wu, Hanxiao Zhang +33

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 o…

eess.IV2022★ 1 cited

Re-thinking and Re-labeling LIDC-IDRI for Robust Pulmonary Cancer Prediction

Hanxiao Zhang, Xiao Gu, Minghui Zhang +6

The LIDC-IDRI database is the most popular benchmark for lung cancer prediction. However, with subjective assessment from radiologists, nodules in LIDC may have entirely different…

eess.IV2022

Faithful learning with sure data for lung nodule diagnosis

Hanxiao Zhang, Liang Chen, Xiao Gu +6

Recent evolution in deep learning has proven its value for CT-based lung nodule classification. Most current techniques are intrinsically black-box systems, suffering from two gene…

eess.IV2022

LTSP: Long-Term Slice Propagation for Accurate Airway Segmentation

Yangqian Wu, Minghui Zhang, Weihao Yu +3

Purpose: Bronchoscopic intervention is a widely-used clinical technique for pulmonary diseases, which requires an accurate and topological complete airway map for its localization…

eess.IV2022

BREAK: Bronchi Reconstruction by gEodesic transformation And sKeleton embedding

Weihao Yu, Hao Zheng, Minghui Zhang +3

Airway segmentation is critical for virtual bronchoscopy and computer-aided pulmonary disease analysis. In recent years, convolutional neural networks (CNNs) have been widely used…

eess.IV2021

FDA: Feature Decomposition and Aggregation for Robust Airway Segmentation

Minghui Zhang, Xin Yu, Hanxiao Zhang +5

3D Convolutional Neural Networks (CNNs) have been widely adopted for airway segmentation. The performance of 3D CNNs is greatly influenced by the dataset while the public airway da…