Segmentation and image analysis of abnormal lungs at CT: current approaches, challenges, and future trends
The computer-based process of identifying the boundaries of lung from surrounding thoracic
tissue on computed tomographic (CT) images, which is called segmentation, is a vital first …
tissue on computed tomographic (CT) images, which is called segmentation, is a vital first …
Computer‐aided diagnosis systems for lung cancer: challenges and methodologies
This paper overviews one of the most important, interesting, and challenging problems in
oncology, the problem of lung cancer diagnosis. Develo** an effective computer-aided …
oncology, the problem of lung cancer diagnosis. Develo** an effective computer-aided …
Knowledge-based collaborative deep learning for benign-malignant lung nodule classification on chest CT
Y ** a data-driven model for lung nodule segmentation
Accurate lung nodule segmentation from computed tomography (CT) images is of great
importance for image-driven lung cancer analysis. However, the heterogeneity of lung …
importance for image-driven lung cancer analysis. However, the heterogeneity of lung …
[PDF][PDF] Early diagnosis of lung cancer with probability of malignancy calculation and automatic segmentation of lung CT scan images
S Manoharan - Journal of Innovative Image Processing (JIIP), 2020 - researchgate.net
Computer aided detection system was developed to identify the pulmonary nodules to
diagnose the cancer cells. Main aim of this research enables an automated image analysis …
diagnose the cancer cells. Main aim of this research enables an automated image analysis …
Early detection of lung cancer using wavelet feature descriptor and feed forward back propagation neural networks classifier
R Arulmurugan, H Anandakumar - Computational vision and bio inspired …, 2018 - Springer
Abstract A Computed Tomography (CT) scan is the most used technique for distinguishing
harmful lung cancer nodules. A Computer Aided Diagnosis (CAD) framework for the …
harmful lung cancer nodules. A Computer Aided Diagnosis (CAD) framework for the …
Dual-branch residual network for lung nodule segmentation
H Cao, H Liu, E Song, CC Hung, G Ma, X Xu, R **… - Applied Soft …, 2020 - Elsevier
An accurate segmentation of lung nodules in computed tomography (CT) images is critical to
lung cancer analysis and diagnosis. However, due to the variety of lung nodules and the …
lung cancer analysis and diagnosis. However, due to the variety of lung nodules and the …
A novel approach to CAD system for the detection of lung nodules in CT images
Detection of pulmonary nodule plays a significant role in the diagnosis of lung cancer in
early stage that improves the chances of survival of an individual. In this paper, a computer …
early stage that improves the chances of survival of an individual. In this paper, a computer …
Volumetric lung nodule segmentation using adaptive roi with multi-view residual learning
Accurate quantification of pulmonary nodules can greatly assist the early diagnosis of lung
cancer, enhancing patient survival possibilities. A number of nodule segmentation …
cancer, enhancing patient survival possibilities. A number of nodule segmentation …