Accurate Segmentation of Brain Tumors in Magnetic Resonance Images with Pyramid Stage Decomposition Network Approach

被引：0

作者：

Ari, Berna Gurler ^{[1
]}

Uzen, Huseyin ^{[2
]}

Sengur, Abdulkadir ^{[3
]}

机构：

[1] Inonu Univ, Bilgisayar Muhendisligi Bolumu, Malatya, Turkiye

[2] Bingo Univ, Bilgisayar Muhendisligi Bolumu, Bingo, Turkiye

[3] Firat Univ, Elekt Elekt Teknol Bolumu, Elazig, Turkiye

来源：

32ND IEEE SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE, SIU 2024 | 2024年

关键词：

Brain tumors; Magnetic Resonance Imaging (MRI); Segmentation; Pyramid Scene Parsing Network (PSPNet); Medical Image Analysis;

D O I：

10.1109/SIU61531.2024.10600920

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This study explores the utilization of the Pyramid Scene Parsing Network (PSPNet) architecture to achieve accurate segmentation of brain tumors in magnetic resonance (MR) images. Experimental evaluations were conducted on different pre-trained backbone network models, including Vgg16, Inceptionv3, Mobilenetv2, Efficientnetb0, Resnet18, Resnet34, Resnet50, Resnet101, Resnext50, and Resnext101, assessing the performance of each model in brain tumor segmentation. The results highlight the VGG16-PSPNet model as the most successful, showcasing high F1-score, mIoU, precision, recall, and accuracy values.

引用

页数：4

共 50 条

[11] Fuzzy clustering approach for brain tumor tissue segmentation in magnetic resonance images
Iván A. Rodríguez-Méndez
Raquel. Ureña
Enrique Herrera-Viedma
Soft Computing, 2019, 23 : 10105 - 10117
[12] Brain Tumor Segmentation Using Graph Coloring Approach in Magnetic Resonance Images
Bagheri, Rouholla
Monfared, Jalal Haghighat
Montazeriyoun, Mohammad Reza
JOURNAL OF MEDICAL SIGNALS & SENSORS, 2021, 11 (04): : 285 - 290
[13] Fuzzy clustering approach for brain tumor tissue segmentation in magnetic resonance images
Rodriguez-Mendez, Ivan A.
Urena, Raquel
Herrera-Viedma, Enrique
SOFT COMPUTING, 2019, 23 (20) : 10105 - 10117
[14] A new approach for analyzing proton magnetic resonance spectroscopic images of brain tumors: nosologic images
Fabien Szabo De Edelenyi
Christophe Rubin
François Estève
Sylvie Grand
Michel Décorps
Virgine Lefournier
Jean-François Le Bas
Chantal Rémy
Nature Medicine, 2000, 6 : 1287 - 1289
[15] A new approach for analyzing proton magnetic resonance spectroscopic images of brain tumors:: nosologic images
De Edeleny, FS
Rubin, C
Estève, F
Grand, S
Décorps, M
Lefournier, V
Le Bas, JF
Rémy, C
NATURE MEDICINE, 2000, 6 (11) : 1287 - 1289
[16] Automatic segmentation of brain tumors in magnetic resonance imaging
Mascarenhas, Layse Ribeiro
Ribeiro Junior, Audenor dos Santos
Ramos, Rodrigo Pereira
EINSTEIN-SAO PAULO, 2020, 18 : eAO4948
[17] Segmentation of Brain Tumor Parts in Magnetic Resonance Images
Mikulka, Jan
Burget, Radim
Riha, Kamil
Gescheidtova, Eva
2013 36TH INTERNATIONAL CONFERENCE ON TELECOMMUNICATIONS AND SIGNAL PROCESSING (TSP), 2013, : 565 - 568
[18] Automatic Segmentation of Neonatal Brain Magnetic Resonance Images
Devi, Chelli N.
Chandrasekharan, Anupama
Sundararaman, V. K.
Alex, Zachariah C.
2014 INTERNATIONAL CONFERENCE ON COMMUNICATIONS AND SIGNAL PROCESSING (ICCSP), 2014,
[19] LEGION - Based segmentation of magnetic resonance images of the brain
Sivaradje, G
Saraswady, D
Dananjayan, P
IETE JOURNAL OF RESEARCH, 2002, 48 (3-4) : 311 - 315
[20] Memory Network-Based Quality Normalization of Magnetic Resonance Images for Brain Segmentation
Su, Yang
Wei, Jie
Ma, Benteng
Xia, Yong
Zhang, Yanning
INTELLIGENCE SCIENCE AND BIG DATA ENGINEERING: VISUAL DATA ENGINEERING, PT I, 2019, 11935 : 58 - 67

← 1 2 3 4 5 →