Original paper
DenseX-Net: An End-to-End Model for Lymphoma Segmentation in Whole-Body PET/CT Images
Abstract
Automatic lymphoma detection and accurate lymphoma boundary delineation from whole body Positron Emission Tomography/Computed Tomography (PET/CT) scans are essential for surgical navigation and radiation therapy. Besides, labeling the data, which means contouring the lymphoma contour in images is time-consuming, operator intensive and subjective. Hence, this paper integrates the supervised learning and unsupervised learning to propose an...
Paper Details
Title
DenseX-Net: An End-to-End Model for Lymphoma Segmentation in Whole-Body PET/CT Images
Published Date
Dec 31, 2019
Journal
Volume
8
Pages
8004 - 8018