Use of Convolutional Neural Networks for Detection and Segmentation of Pulmonary Nodules in Computed Tomography Images

被引：0

作者：

Saraiva, A. A. ^{[2
,6
]}

Lopes, Luciano ^{[1
]}

Pedro, Pimentel ^{[1
]}

Moura Sousa, Jose Vigno ^{[1
]}

Fonseca Ferreira, N. M. ^{[3
,4
]}

Batista Neto, J. E. S. ^{[6
]}

Soares, Salviano ^{[3
]}

Valente, Antonio ^{[2
,5
]}

机构：

[1] UESPI Univ State Piaui, Piripiri, Brazil

[2] Univ Tras Os Montes & Alto Douro, Vila Real, Portugal

[3] Coimbra Polytech, ISEC, Coimbra, Portugal

[4] Polytech Inst Porto, Knowledge Engn & Decis Support Res Ctr GECAD, Inst Engn, Porto, Portugal

[5] INESC TEC Technol & Sci, Porto, Portugal

[6] Univ Sao Paulo, Sao Carlos, Brazil

来源：

BIODEVICES: PROCEEDINGS OF THE 13TH INTERNATIONAL JOINT CONFERENCE ON BIOMEDICAL ENGINEERING SYSTEMS AND TECHNOLOGIES, VOL 1: BIODEVICES, 2020 | 2020年

关键词：

UNet; Segmentation; CT Scanner; Lung Nodes;

D O I：

10.5220/0009178902920297

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

This paper presents a method capable of detecting and segmenting pulmonary nodules in clinical computed tomography images, using UNet convolutional neural network powered by The Lung Image Database Consortium image collection - LIDC-IDRI, that in the training process was submitted to different training tests, where for each of them, their hyper-parameters were modified so that the results could be collected from different media, getting quite satisfactory results in the segmentation task, highlighting the areas of interest almost perfectly, resulting in 91.61% on the IoU (Intersection over Union) metric.

引用

页码：292 / 297

页数：6

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