Computer-aided diagnosis of lung cancer and pulmonary embolism in computed tomography - A review

被引:58
作者
Chan, Heang-Ping [1 ]
Hadjiiski, Lubomir [1 ]
Zhou, Chuan [1 ]
Sahiner, Berkman [1 ]
机构
[1] Univ Michigan, Dept Radiol, Ann Arbor, MI 48109 USA
关键词
CAD; lung nodule; pulmonary embolism; CT;
D O I
10.1016/j.acra.2008.01.014
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Computer-aided detection (CADe) and computer-aided diagnosis (CADx) have been important areas of research in the last two decades. Significant progress has been made in the area of breast cancer detection, and CAD techniques are being developed in many other areas. Recent advances in multidetector row computed tomography have made it an increasingly common modality for imaging of lung diseases. A thoracic examination using thin-section computed tomography contains hundreds of images. Detection of lung cancer and pulmonary embolism on computed tomographic (CT) examinations are demanding tasks for radiologists because they have to search for abnormalities in a large number of images, and the lesions can be subtle. If successfully developed, CAD can be a useful second opinion to radiologists in thoracic CT interpretation. In this review, we summarize the studies that have been reported in these areas, discuss some challenges in the development of CAD, and identify areas that deserve particular attention in future research.
引用
收藏
页码:535 / 555
页数:21
相关论文
共 159 条
[51]   DETERMINING THE LIKELIHOOD OF MALIGNANCY IN SOLITARY PULMONARY NODULES WITH BAYESIAN-ANALYSIS .2. APPLICATION [J].
GURNEY, JW ;
LYDDON, DM ;
MCKAY, JA .
RADIOLOGY, 1993, 186 (02) :415-422
[52]   SOLITARY PULMONARY NODULES - DETERMINING THE LIKELIHOOD OF MALIGNANCY WITH NEURAL-NETWORK ANALYSIS [J].
GURNEY, JW ;
SWENSEN, SJ .
RADIOLOGY, 1995, 196 (03) :823-829
[53]   DETERMINING THE LIKELIHOOD OF MALIGNANCY IN SOLITARY PULMONARY NODULES WITH BAYESIAN-ANALYSIS .1. THEORY [J].
GURNEY, JW .
RADIOLOGY, 1993, 186 (02) :405-413
[54]   Missed lung cancer at CT: Imaging findings in nine patients [J].
Gurney, JW .
RADIOLOGY, 1996, 199 (01) :117-122
[55]  
HADJIISKI LM, 2007, P SOC PHOTO-OPT INS, V6514, P111
[56]   Neural networks for the analysis of small pulmonary nodules [J].
Henschke, CI ;
Yankelevitz, DF ;
Mateescu, I ;
Brettle, DW ;
Rainey, TG ;
Weingard, FS .
CLINICAL IMAGING, 1997, 21 (06) :390-399
[57]   Early Lung Cancer Action Project: overall design and findings from baseline screening [J].
Henschke, CI ;
McCauley, DI ;
Yankelevitz, DF ;
Naidich, DP ;
McGuinness, G ;
Miettinen, OS ;
Libby, DM ;
Pasmantier, MW ;
Koizumi, J ;
Altorki, NK ;
Smith, JP .
LANCET, 1999, 354 (9173) :99-105
[58]  
Henschke CI, 2006, NEW ENGL J MED, V355, P1763, DOI 10.1056/NEJMoa060476
[59]   A NONINVASIVE STRATEGY FOR THE TREATMENT OF PATIENTS WITH SUSPECTED PULMONARY-EMBOLISM [J].
HULL, RD ;
RASKOB, GE ;
GINSBERG, JS ;
PANJU, AA ;
BRILLEDWARDS, P ;
COATES, G ;
PINEO, GF .
ARCHIVES OF INTERNAL MEDICINE, 1994, 154 (03) :289-297
[60]  
JEUDY J, 2006, RSNA PROGRAM BOK, P255