Multi-site, multi-domain airway tree modeling
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 …
vision and image analysis algorithms. In recent years, new methods have extended the …
Artificial intelligence in COPD CT images: identification, staging, and quantitation
Chronic obstructive pulmonary disease (COPD) stands as a significant global health
challenge, with its intricate pathophysiological manifestations often demanding advanced …
challenge, with its intricate pathophysiological manifestations often demanding advanced …
Naviairway: a bronchiole-sensitive deep learning-based airway segmentation pipeline
Airway segmentation is essential for chest CT image analysis. Different from natural image
segmentation, which pursues high pixel-wise accuracy, airway segmentation focuses on …
segmentation, which pursues high pixel-wise accuracy, airway segmentation focuses on …
Multi-site, multi-domain airway tree modeling (ATM'22): a public benchmark for pulmonary airway segmentation
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 …
vision and image analysis algorithms. In recent years, new methods have extended the …
Diabetic retinopathy lesion segmentation using deep multi-scale framework
The segmentation of diabetic retinopathy (DR) lesions is important for large-scale screening
using color fundus photography (CFP) images. The difficulty of this task is that the DR …
using color fundus photography (CFP) images. The difficulty of this task is that the DR …
Interpolation-split: a data-centric deep learning approach with big interpolated data to boost airway segmentation performance
The morphology and distribution of airway tree abnormalities enable diagnosis and disease
characterisation across a variety of chronic respiratory conditions. In this regard, airway …
characterisation across a variety of chronic respiratory conditions. In this regard, airway …
Towards connectivity-aware pulmonary airway segmentation
Detailed pulmonary airway segmentation is a clinically important task for endobronchial
intervention and treatment of peripheral pulmonary lesions. Convolutional Neural Networks …
intervention and treatment of peripheral pulmonary lesions. Convolutional Neural Networks …
An end-to-end multi-scale airway segmentation framework based on pulmonary CT image
Objective. Automatic and accurate airway segmentation is necessary for lung disease
diagnosis. The complex tree-like structures leads to gaps in the different generations of the …
diagnosis. The complex tree-like structures leads to gaps in the different generations of the …
Extraction of pulmonary airway in CT scans using deep fully convolutional networks
S Yuan - arXiv preprint arXiv:2208.07202, 2022 - arxiv.org
Accurate, automatic and complete extraction of pulmonary airway in medical images plays
an important role in analyzing thoracic CT volumes such as lung cancer detection, chronic …
an important role in analyzing thoracic CT volumes such as lung cancer detection, chronic …
A data-centric deep learning approach to airway segmentation
The morphology and distribution of airway tree abnormalities enables diagnosis and
disease characterisation across a variety of chronic respiratory conditions. In this regard …
disease characterisation across a variety of chronic respiratory conditions. In this regard …