电子学报 ›› 2018, Vol. 46 ›› Issue (6): 1319-1326.DOI: 10.3969/j.issn.0372-2112.2018.06.007
彭圆圆, 肖昌炎
收稿日期:
2016-07-05
修回日期:
2017-10-16
出版日期:
2018-06-25
通讯作者:
作者简介:
基金资助:
PENG Yuan-yuan, XIAO Chang-yan
Received:
2016-07-05
Revised:
2017-10-16
Online:
2018-06-25
Published:
2018-06-25
Corresponding author:
Supported by:
摘要: CT(Computer Tomography)图像中自动分割肺裂是很困难的,肺裂往往存在不完整、形变、断裂和附裂等现象.本文提出一种融合肺部解剖结构特征来实现自动分割肺裂的方法.首先结合肺部气管和动脉血管信息定位肺裂感兴趣区域.然后利用肺裂方向信息增强肺裂,并利用多剖面滤波器滤除噪声从而对肺裂进行预分割.最后融合已定位的肺裂感兴趣区域和肺裂预分割结果来自动分割肺裂.与人工参考对比,提出的算法在人体左肺和右肺中分割的肺裂的F1-score中值分别为0.881和0.878.
中图分类号:
彭圆圆, 肖昌炎. 一种全自动的肺裂分割方法[J]. 电子学报, 2018, 46(6): 1319-1326.
PENG Yuan-yuan, XIAO Chang-yan . Automatic Segmentation of Pulmonary Fissures in CT Chest Images[J]. Acta Electronica Sinica, 2018, 46(6): 1319-1326.
[1] DOEL T,GAVAGHAN D J,GRAU V.Review of automatic pulmonary lobe segmentation methods from CT[J].Computerized Medical Imaging and Graphics,2015,40:13-29. [2] QI S,VAN TRIEST H J,YUE Y,MINGJIE X,YAN K.Automatic pulmonary fissure detection and lobe segmentation in CT chest images[J].BioMedical Engineering OnLine,2014,13:59-69. [3] WIEMKER R,BULOW T,BLAFFERT T.Unsupervised extraction of the pulmonary interlobar fissures from high resolution thoracic CT data[A].International Congress Series[C].New York:Elsevier,2005.1121-1126. [4] 贾同,魏颖,赵大哲.一种基于CT影像的肺癌病灶检测新方法[J].电子学报,2010,38(11):2545-2549. JIA Tong,WEI Ying,ZHAO Da-zhe.A new Lung Cancer lesions detection scheme based on CT image[J].Acta Electronica Sinica,2010,38(11):2545-2549.(in Chinese) [5] CRONIN P,GROSS B H,KELLY A M,et al.Normal and accessory fissures of the lung:evaluation with contiguous volumetric thin-section multidetector CT[J].European Journal of Radiology,2010,75(2):1-8. [6] ZHANG L,HOFFMAN E A,REINHARDT J M.Atlas-driven lung lobe segmentation in volumetric X-ray CT images[J].IEEE Transactions on Medical Imaging,2006,25(1):1-16. [7] WANG J,BETKE M,KO J P.Pulmonary fissure segmentation on CT[J].Med Image Anal,2006,10:530-547. [8] VAN RIKXOORT E M,PROKOP M,De Hoop B,et al.Automatic segmentation of pulmonary lobes robust against incomplete fissures[J].IEEE Transactions on Medical Imaging,2010,29(6):1286-1296. [9] LASSEN B,VAN RIKXOORT E M,SCHMIDT M,et al.Automatic segmentation of the pulmonary lobes from chest CT scans based on fissures,vessels,and bronchi[J].IEEE Transactions on Medical Imaging,2013,32(2):210-222. [10] PU J,LEADER J K,ZHENG B,et al.A computational geometry approach to automated pulmonary fissure segmentation in CT examinations[J].IEEE Transactions on Medical Imaging,2009,28(5):710-719. [11] GU S,WILSON D,WANG Z,et al.Identification of pulmonary fissures using a piecewise plane fitting algorithm[J].Computerized Medical Imaging and Graphics,2012,36(7):560-571. [12] KLINDER T,HANNES W,AND RAFAEL W.Lobar fissure detection using line enhancing filters[A].International Society for Optics and Photonics[C].Florida:SPIE,2013.86693C. [13] XIAO C,STARING M,WANG J,et al.A derivative of stick filter for pulmonary fissure detection in CT images[A].International Society for Optics and Photonics[C].Florida:SPIE,2013.86690V_1-86690V_9. [14] XIAO C,STOEL B C,BAKKER M E,et al.Pulmonary fissure detection in CT images using a derivative of stick filter[J].IEEE Transactions on Medical Imaging,2016,35(6):1488-1500. [15] 周寿军,陈武凡,冯前进,等.基于概率跟踪的冠状动脉造影图像的血管树提取[J].电子学报,2006,34(7):1270-1274. ZHOU Shou-jun,CHEN Wu-fan,FENG Qian-jin,et al.Extracting the coronary artery tree in angiographic projections based on probability tracking[J].Acta Electronica Sinica,2006,34(7):1270-1274.(in Chinese) [16] SMISTAD E,ELSTER A C,LINDSETH F.GPU-based airway segmentation and centerline extraction for image guided bronchoscopy[A].Norsk Informatikkonferanse Conference[C].US:NIK,2012.129-140. [17] BAUER C,POCK T,SORANTIN E,et al.Segmentation of interwoven 3d tubular tree structures utilizing shape priors and graph cuts[J].Medical Image Analysis,2010,14:172-184. [18] EDELSBRUNNER H,MVCKE E P.Three-dimensional alpha shapes[J].ACM Transactions on Graphics,1994,13(1):43-72. [19] XU C,PRINCE J L.Snakes,shapes,and gradient vector flow[J].IEEE Transactions on Image Processing,1998,7(3):359-369. [20] KRISSIAN K,MALANDAIN G,AYACHE N,et al.Model-based detection of tubular structures in 3D images[J].Computer Vision and Image Understanding,2000,80(2):130-171. [21] TSCHIRREN J,MCLENNAN G,PALáGYI K,et al.Matching and anatomical labeling of human airway tree[J].IEEE Transactions on Medical Imaging,2005,24(12):1540-1547. [22] KITAMURA Y,LI Y,ITO W,et al.Data-dependent higher-order clique selection for artery-vein segmentation by energy minimization[J].International Journal of Computer Vision,2015,1:1-17. |
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