Paper Info
Title
Tuberculosis CT Image Analysis Using Image Features Extracted by 3D Autoencoder.
Abstract
This paper presents an approach for the automated analysis of 3D Computed Tomography (CT) images based on the utilization of descriptors extracted using 3D deep convolutional autoencoder (AEC [8]) networks. Both the common flow of AEC model application and a set of techniques for overcoming the lack of training samples are presented in this work. The described approach was used for accomplishing the two subtasks of the ImageCLEF 2019: Tuberculosis competition [2, 5] and allowed to achieve the 2nd best performance in the TB Severity Scoring subtask and the 6th best performance in the TB CT Report subtask.
Year
DOI
Venue
2020
10.1007/978-3-030-58219-7_12
CLEF
DocType
Citations 
PageRank 
Conference
0
0.34
References 
Authors
0
1
Name
Order
Citations
PageRank
Siarhei Kazlouski100.34