Deep multi-scale location-aware 3D convolutional neural networks for automated detection of lacunes of presumed vascular origin

被引:94
作者
Ghafoorian, Mohsen [1 ,2 ]
Karssemeijer, Nico [2 ]
Heskes, Tom [1 ]
Bergkamp, Mayra [3 ]
Wissink, Joost [3 ]
Obels, Jiri [2 ]
Keizer, Karlijn [3 ]
de Leeuw, Frank-Erik [3 ]
van Ginneken, Bram [2 ]
Marchiori, Elena [1 ]
Platel, Bram [2 ]
机构
[1] Radboud Univ Nijmegen, Inst Comp & Informat Sci, Nijmegen, Netherlands
[2] Radboud Univ Nijmegen, Med Ctr, Diagnost Image Anal Grp, Dept Radiol & Nucl Med, Nijmegen, Netherlands
[3] Radboud Univ Nijmegen, Med Ctr, Dept Neurol, Donders Inst Brain Cognit & Behav, Nijmegen, Netherlands
关键词
Lacunes; Automated detection; Convolutional neural networks; Deep learning; Multi-scale; Location-aware; AIDED DIAGNOSIS SCHEME; ENCODER NETWORKS; BRAIN; INFARCTS; SEGMENTATION; DISEASE; LESIONS; IMAGES;
D O I
10.1016/j.nicl.2017.01.033
中图分类号
R445 [影像诊断学];
学科分类号
100207 ;
摘要
Lacunes of presumed vascular origin (lacunes) are associated with an increased risk of stroke, gait impairment, and dementia and are a primary imaging feature of the small vessel disease. Quantification of lacunes may be of great importance to elucidate the mechanisms behind neuro-degenerative disorders and is recommended as part of study standards for small vessel disease research. However, due to the different appearance of lacunes in various brain regions and the existence of other similar-looking structures, such as perivascular spaces, manual annotation is a difficult, elaborative and subjective task, which can potentially be greatly improved by reliable and consistent computer-aided detection (CAD) routines. In this paper, we propose an automated two-stage method using deep convolutional neural networks (CNN). We show that this method has good performance and can considerably benefit readers. We first use a fully convolutional neural network to detect initial candidates. In the second step, we employ a 3D CNN as a false positive reduction tool. As the location information is important to the analysis of candidate structures, we further equip the network with contextual information using multi-scale analysis and integration of explicit location features. We trained, validated and tested our networks on a large dataset of 1075 cases obtained from two different studies. Subsequently, we conducted an observer study with four trained observers and compared our method with them using a free-response operating characteristic analysis. Shown on a test set of 111 cases, the resulting CAD system exhibits performance similar to the trained human observers and achieves a sensitivity of 0.974 with 0.13 false positives per slice. A feasibility study also showed that a trained human observer would considerably benefit once aided by the CAD system. (C) 2017 The Authors. Published by Elsevier Inc.
引用
收藏
页码:391 / 399
页数:9
相关论文
共 53 条
[1]  
[Anonymous], 2016, ARXIV160305959
[2]  
[Anonymous], ARXIV161004834
[3]  
[Anonymous], 2015, ARXIV150503229
[4]   INCIDENTAL SUBCORTICAL LESIONS IDENTIFIED ON MAGNETIC-RESONANCE-IMAGING IN THE ELDERLY .2. POSTMORTEM PATHOLOGICAL CORRELATIONS [J].
AWAD, IA ;
JOHNSON, PC ;
SPETZLER, RF ;
HODAK, JA .
STROKE, 1986, 17 (06) :1090-1097
[5]   Large-Scale Machine Learning with Stochastic Gradient Descent [J].
Bottou, Leon .
COMPSTAT'2010: 19TH INTERNATIONAL CONFERENCE ON COMPUTATIONAL STATISTICS, 2010, :177-186
[6]   Deep 3D Convolutional Encoder Networks With Shortcuts for Multiscale Feature Integration Applied to Multiple Sclerosis Lesion Segmentation [J].
Brosch, Tom ;
Tang, Lisa Y. W. ;
Yoo, Youngjin ;
Li, David K. B. ;
Traboulsee, Anthony ;
Tam, Roger .
IEEE TRANSACTIONS ON MEDICAL IMAGING, 2016, 35 (05) :1229-1239
[7]   Deep Convolutional Encoder Networks for Multiple Sclerosis Lesion Segmentation [J].
Brosch, Tom ;
Yoo, Youngjin ;
Tang, Lisa Y. W. ;
Li, David K. B. ;
Traboulsee, Anthony ;
Tam, Roger .
MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION, PT III, 2015, 9351 :3-11
[8]   Silent Infarcts and Cerebral Microbleeds Modify the Associations of White Matter Lesions With Gait and Postural Stability Population-Based Study [J].
Choi, Philip ;
Ren, Mandy ;
Phan, Thanh G. ;
Callisaya, Michele ;
Ly, John V. ;
Beare, Richard ;
Chong, Winston ;
Srikanth, Velandai .
STROKE, 2012, 43 (06) :1505-+
[9]  
Ciresan D., 2013, MULTICOLUMN DEEP NEU
[10]  
Ciresan D., 2012, Advances in Neural Information Processing Systems 25 (NIPS 2012), P1