Preoperative Volume Determination for Pituitary Adenoma

被引:5
作者
Zukic, Dzenan [1 ]
Egger, Jan [2 ,3 ]
Bauer, Miriam H. A. [2 ,3 ]
Kuhnt, Daniela [2 ]
Carl, Barbara [2 ]
Freisleben, Bernd [3 ]
Kolb, Andreas [1 ]
Nimsky, Christopher [2 ]
机构
[1] Univ Siegen, Comp Graph Grp, Holderlinstr 3, D-57076 Siegen, Germany
[2] Univ Marburg, Dept Neurosurg, D-35033 Marburg, Germany
[3] Univ Marburg, Dept Math & Comp Sci, D-35032 Marburg, Germany
来源
MEDICAL IMAGING 2011: COMPUTER-AIDED DIAGNOSIS | 2011年 / 7963卷
关键词
Pituitary Adenoma; Preoperative; Volume Determination; MRI; Balloon Inflation;
D O I
10.1117/12.877660
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The most common sellar lesion is the pituitary adenoma, and sellar tumors are approximately 10-15% of all intracranial neoplasms. Manual slice-by-slice segmentation takes quite some time that can be reduced by using the appropriate algorithms. In this contribution, we present a segmentation method for pituitary adenoma. The method is based on an algorithm that we have applied recently to segmenting glioblastoma multiforme. A modification of this scheme is used for adenoma segmentation that is much harder to perform, due to lack of contrast-enhanced boundaries. In our experimental evaluation, neurosurgeons performed manual slice-by-slice segmentation of ten magnetic resonance imaging (MRI) cases. The segmentations were compared to the segmentation results of the proposed method using the Dice Similarity Coefficient (DSC). The average DSC for all datasets was 75.92%+/- 7.24%. A manual segmentation took about four minutes and our algorithm required about one second.
引用
收藏
页数:7
相关论文
共 16 条
[1]   Glioma dynamics and computational models:: a review of segmentation, registration, and in silico growth algorithms and their clinical applications [J].
Angelini, Elsa D. ;
Clatz, Olivier ;
Mandonnet, Emmanuel ;
Konukoglu, Ender ;
Capelle, Laurent ;
Duffau, Hugues .
CURRENT MEDICAL IMAGING REVIEWS, 2007, 3 (04) :262-276
[2]  
[Anonymous], P INT BIOS PROC C
[3]   The cytogenesis and pathogenesis of pituitary adenomas [J].
Asa, SL ;
Ezzat, S .
ENDOCRINE REVIEWS, 1998, 19 (06) :798-827
[4]   An experimental comparison of min-cut/max-flow algorithms for energy minimization in vision [J].
Boykov, Y ;
Kolmogorov, V .
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2004, 26 (09) :1124-1137
[5]   Surgical treatment of pituitary tumours [J].
Buchfelder, Michael ;
Schlaffer, Sven .
BEST PRACTICE & RESEARCH CLINICAL ENDOCRINOLOGY & METABOLISM, 2009, 23 (05) :677-692
[6]   ON ACTIVE CONTOUR MODELS AND BALLOONS [J].
COHEN, LD .
CVGIP-IMAGE UNDERSTANDING, 1991, 53 (02) :211-218
[7]  
Descoteaux Maxime, 2006, Comput Aided Surg, V11, P247, DOI 10.3109/10929080601017212
[8]  
Egger J, 2010, LNCS, V6376, P383
[9]  
Egger J., 2010, P INT BIOS PROC C CH
[10]  
Felkel P, 2001, COMPUT GRAPH FORUM, V20, pC26, DOI 10.1111/1467-8659.00495