Feature Selection for Automatic CT-based Prostate Segmentation

被引：0

作者：

Kos, Artur ^{[1
]}

Skalski, Andrzej ^{[2
]}

Zielinski, Tomasz P. ^{[1
]}

Gomes, Diana ^{[3
]}

Sa, Vitor ^{[3
]}

Kedzierawski, Piotr ^{[4
]}

Kuszewski, Tomasz ^{[5
]}

机构：

[1] AGH Univ Sci & Technol, Dept Telecommun, Krakow, Poland

[2] AGH Univ Sci & Technol, Dept Measurement & Elect, Krakow, Poland

[3] Univ Porto, Fac Engn, Oporto, Portugal

[4] Holly Cross Canc Ctr, Dept Radiotherapy, Kielce, Poland

[5] Holly Cross Canc Ctr, Dept Med Phys, Kielce, Poland

来源：

2016 IEEE INTERNATIONAL CONFERENCE ON IMAGING SYSTEMS AND TECHNIQUES (IST) | 2016年

关键词：

feature selection; prostate segmentation; computed tomography; radiotherapy;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The paper addresses a problem of feature selection for automatic prostate segmentation in Computed Tomography (CT) planning data for radiotherapy process. The following image descriptors have been tested in 2D and 3D scenarios: standard Hounsfield Unit (HU) profiles, histogram of oriented gradient (HoG), Haar wavelets, and Modality Independent Neighborhood Descriptor (MIND). The task was to distinguish a prostate interior and exterior. 22 CT volumes with different spatial resolution and different organ outlines have been used. The k-Nearest Neighbors (kNN) classifier was applied and the following recognition measures were evaluated, with 10-fold cross-validation: accuracy, precision, sensitivity and specificity.

引用

页码：243 / 248

页数：6

共 24 条

[1] Wavelet-based algorithm to the evaluation of contrasted hepatocellular carcinoma in CT-images after transarterial chemoembolization
Alvarez, Matheus
de Pina, Diana Rodrigues
Romeiro, Fernando Gomes
Duarte, Sergio Barbosa
de Arruda Miranda, Jose Ricardo
[J]. RADIATION ONCOLOGY, 2014, 9
[2] Antonakos E., 2014, IM PROC ICIP 2014 IE
[3] Feature-Based Lucas-Kanade and Active Appearance Models
Antonakos, Epameinondas
Alabort-i-Medina, Joan
Tzimiropoulos, Georgios
Zafeiriou, Stefanos P.
[J]. IEEE TRANSACTIONS ON IMAGE PROCESSING, 2015, 24 (09) : 2617 - 2632
[4] Segmenting the prostate and rectum in CT imagery using anatomical constraints
Chen, Siqi
Lovelock, D. Michael
Radke, Richard J.
[J]. MEDICAL IMAGE ANALYSIS, 2011, 15 (01) : 1 - 11
[5] ACTIVE SHAPE MODELS - THEIR TRAINING AND APPLICATION
COOTES, TF
TAYLOR, CJ
COOPER, DH
GRAHAM, J
[J]. COMPUTER VISION AND IMAGE UNDERSTANDING, 1995, 61 (01) : 38 - 59
[6] Feulner J, 2009, LECT NOTES COMPUT SC, V5761, P255, DOI 10.1007/978-3-642-04268-3_32
[7] Ghose S., 2010, SIGN IM TECHN INT BA
[8] A survey of prostate segmentation methodologies in ultrasound, magnetic resonance and computed tomography images
Ghose, Soumya
Oliver, Arnau
Marti, Robert
Llado, Xavier
Vilanova, Joan C.
Freixenet, Jordi
Mitra, Jhimli
Sidibe, Desire
Meriaudeau, Fabrice
[J]. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, 2012, 108 (01) : 262 - 287
[9] Evaluation of atlas-based auto-segmentation software in prostate cancer patients
Greenham, Stuart
Dean, Jenna
Fu, Cheuk Kuen Kenneth
Goman, Joanne
Mulligan, Jeremy
Tune, Deanna
Sampson, David
Westhuyzen, Justin
Mckay, Michael
[J]. JOURNAL OF MEDICAL RADIATION SCIENCES, 2014, 61 (03): : 151 - 158
[10] On the theory of orthogonal function systems (First announcement)
Haar, A
[J]. MATHEMATISCHE ANNALEN, 1910, 69 : 331 - 371

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