Knowledge-driven segmentation of the central sulcus from human brain MR images

被引：0

作者：

Zuo, W ^{[1
]}

Hu, QM ^{[1
]}

Aziz, A ^{[1
]}

Loe, K ^{[1
]}

Nowinski, WL ^{[1
]}

机构：

[1] Bioinformat Inst, Biomed Imaging Grp, Singapore, Singapore

来源：

ICIP: 2004 INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOLS 1- 5 | 2004年

关键词：

central sulcas; segmentation; MRI; human brain; neuroinformatics;

D O I：

暂无

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

This paper presents a knowledge-driven algorithm to identify and segment the central suclus (CS) from human brain MR images. The dataset is reformatted along the anterior and posterior commissures (AC-PC) plane first. Then, the 3D region within the two coronal planes passing through the AC and PC is defined as the region of interest (ROI) to search for all the sulci within it. The CS is the suclus with the largest volume within the ROI. Together with the sulci, grey matter (GM) is included for the region growing in order to deal with the partial volume effect. The GM is removed through skeletonization. Experimental results are given.

引用

页码：2443 / 2446

页数：4

共 50 条

[21] Considering the variability of the collateral sulcus in the segmentation of parahippocampal cortex structures from MR images
Pruessner, J
Koehler, S
Hampel, H
Teipel, SJ
Buerger, K
Collins, DL
Evans, AC
NEUROBIOLOGY OF AGING, 2004, 25 (02) : 254 - 254
[22] Automated Segmentation of the Lateral Ventricle in MR images of Human Brain
Gan, Ke
2015 IEEE INTERNATIONAL CONFERENCE ON DIGITAL SIGNAL PROCESSING (DSP), 2015, : 139 - U1320
[23] Knowledge-Driven Activity Recognition and Segmentation Using Context Connections
Meditskos, Georgios
Kontopoulos, Efstratios
Kompatsiaris, Ioannis
SEMANTIC WEB - ISWC 2014, PT II, 2014, 8797 : 260 - 275
[24] Automated segmentation of the cerebrospinal fluid and the lateral ventricles from human brain MR images
Kobashi, S
Takae, T
Hata, Y
Kitamura, YT
Yanagida, T
Ishikawa, O
Ishikawa, M
JOINT 9TH IFSA WORLD CONGRESS AND 20TH NAFIPS INTERNATIONAL CONFERENCE, PROCEEDINGS, VOLS. 1-5, 2001, : 1961 - 1966
[25] Knowledge-driven, interactive animation of human running
Bruderlin, A
Calvert, T
GRAPHICS INTERFACE '96, PROCEEDINGS, 1996, : 213 - 221
[26] Automated segmentation of brain MR images
Tsai, C
Manjunath, BS
Jagadeesan, R
PATTERN RECOGNITION, 1995, 28 (12) : 1825 - 1837
[27] Segmentation of Brain Lesions in MR Images
Tripathi, Sweta
Anand, R. S.
Fernandez, E.
2018 INTERNATIONAL CONFERENCE ON RECENT INNOVATIONS IN ELECTRICAL, ELECTRONICS & COMMUNICATION ENGINEERING (ICRIEECE 2018), 2018, : 1684 - 1688
[28] Segmentation and volume estimation of brain tissues from MR images
Smitha, S. S.
Revathy, K.
Kesavadas, C.
IMECS 2006: INTERNATIONAL MULTICONFERENCE OF ENGINEERS AND COMPUTER SCIENTISTS, 2006, : 543 - +
[29] INTERACTIVE SEGMENTATION OF MR IMAGES FROM BRAIN TUMOR PATIENTS
Bauer, Stefan
Porz, Nicole
Meier, Raphael
Pica, Alessia
Slotboom, Johannes
Wiest, Roland
Reyes, Mauricio
2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI), 2014, : 862 - 865
[30] Geographical Knowledge-Driven Representation Learning for Remote Sensing Images
Li, Wenyuan
Chen, Keyan
Chen, Hao
Shi, Zhenwei
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2022, 60

← 1 2 3 4 5 →