This approach retrieves and displays nodules that exhibit morphological and internal profiles consistent to the nodule in question. It uses a three-dimensional ...
Abstract. The purpose of this study is to develop an image-guided decision support system that assists decision-making in clinical differential diagnosis of.
Jan 11, 2024 · Initially, three anatomical planes (axial, coronal, and sagittal) of pulmonary nodules are extracted from 3-D CT image volumes. Subsequently ...
Feb 15, 2021 · In this paper, we propose a computer-aided classification method for lung nodules using expert knowledge.
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Example-based assisting approach for pulmonary nodule classification in three-dimensional thoracic computed tomography images. · Three-dimensional CT image ...
Jul 11, 2020 · We present a deep learning system that transforms a 3D image of a pulmonary nodule from a CT scan into a low-dimensional embedding vector.
Dec 4, 2022 · We propose a deep convolutional neural network technique (TransUnet) to automatically classify lung nodules accurately.
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It uses a 3D computed tomography image database containing 143 pulmonary nodules for which diagnosis is known. The central module makes possible analysis of the ...
Oct 16, 2021 · Added value of computer-aided CT image features for early lung cancer diagnosis with small pulmonary nodules: a matched case-control study.
The lung nodules labelled as class 1 and 2 are considered as benign nodules, and those labelled as class 4 and 5 are considered as malignant nodules. Lung ...