2024年5月1日 · Pulmonary segments are a functionally independent unit of the lung, supplied by their own segmental bronchus and pulmonary artery and with their own venous and lymphatic drainage. This allows for loss of a segment, without affecting the adjacent segments.

2018年1月1日 · Lung CT image segmentation is a necessary initial step for lung image analysis, it is a prerequisite step to provide an accurate lung CT image analysis such as lung cancer detection. In this work, we propose a lung CT image segmentation using the U-net architecture, one of the most used architectures in deep learning for image segmentation.

2020年8月20日 · Automated segmentation of anatomical structures is a crucial step in image analysis. For lung segmentation in computed tomography, a variety of approaches exists, involving sophisticated pipelines trained and validated on different datasets. However, the clinical applicability of these approaches across diseases remains limited.

2022年5月23日 · The automatic lung segmentation model performs poorly in processing images of some diseases, such as pulmonary consolidation, lung effect, lung edema, and atelectasis.

In this study, the performance of a fully automatic framework for lung field segmentation in chest X-ray images was evaluated. The framework is rooted in the combination of the Segment Anything Model (SAM) with prompt capabilities, and the You Only Look Once (YOLO) model to provide effective prompts.

2023年4月10日 · This work aims to develop a computationally efficient and robust deep learning model for lung segmentation using chest computed tomography (CT) images with DeepLabV3 + networks for two-class (background and lung field) and four-class (ground-glass opacities, background, consolidation, and lung field).

We presented an extensive systematic review of automated lung segmentation in CT images, answering the research question: “What are the quantitatively evaluated, computed, and automated segmentation methods for the lung and its lobes and findings, using computed tomography images?”.

Image segmentation is an essential step in quantifying the extent of reduced or absent lung function. The aim of this study is to develop and validate a new tool for automatic segmentation of lungs in ventilation and perfusion SPECT images and ...

2023年7月21日 · The automatic segmentation of lung lesions in CT images, including COVID-19 pneumonia and other lesions with similar CT findings, such as tuberculosis and pulmonary nodules, has always been challenging because of the various morphologies, intensities, and locations of lung lesions. 1 Traditional morphology-based segmentation methods, such as ...

In chest X-rays, accurate and automatic segmentation is challenging due to variances in lung shape caused by health issues. To improve the precision of segmenting the lung region of chest radiographs, we propose an improved DeeplabV3+ model to implement semantic segmentation for chest radiographic images.