Factors Influencing Lesion Detection in SPECT Lung Images

被引:0
作者
Gifford, H. C. [1 ]
Zheng, X. M. [2 ]
Licho, R. [1 ]
Pretorius, P. H. [1 ]
Schneider, P. B. [1 ]
Simkin, P. H. [1 ]
King, M. A. [1 ]
机构
[1] Univ Massachusetts, Sch Med, Dept Radiol, Worcester, MA 01605 USA
[2] Charles Sturt Univ, Sch Clin Sci, Wagga Wagga, NSW, Australia
来源
2006 IEEE NUCLEAR SCIENCE SYMPOSIUM CONFERENCE RECORD, VOL 1-6 | 2006年
关键词
D O I
10.1109/NSSMIC.2006.356429
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
An earlier localization ROC (LROC) study that found attenuation correction (AC) degraded the detection of solitary pulmonary nodules (SPN) in hybrid SPECT lung images had several potential shortcomings related to the simulation methods. We sought to address these issues with a revised LROC study. Clinical Tc-99m NeoTect scans acquired with a simultaneous transmission-emission protocol defined the normal cases in a single-slice LROC study. Abnormal cases contained a simulated 1-cm lung lesion. Four rescaled-block-iterative EM (RBI) reconstruction strategies applied: 1) AC, scatter correction (SC), and resolution compensation (RC); 2) AC only; 3) RC only; and 4) no corrections (NC). Images from these strategies underwent 3D Gaussian post-smoothing. Performances were defined by the average area under the LROC curve obtained from three human observers. The strategy ranking in order of decreasing performance was: 1) RBI with RC; 2) RBI with all corrections; 3) RBI with AC; and 4) RBI with no corrections. A multireader-multicase (MRMC) analysis only found significant patient and patient-strategy effects. The conflicting results concerning AC from this study and the previous one may revolve around lesion masking effects, which, by design, were not a factor in the current study.
引用
收藏
页码:2662 / 2666
页数:5
相关论文
共 50 条
[21]   A computer model of lung morphology to analyze SPECT images [J].
Schroeter, JD ;
Fleming, JS ;
Hwang, DM ;
Martonen, TB .
COMPUTERIZED MEDICAL IMAGING AND GRAPHICS, 2002, 26 (04) :237-246
[22]   An evaluation of iterative reconstruction strategies based on mediastinal lesion detection using hybrid Ga-67 SPECT images [J].
Pereira, Nicholas F. ;
Gifford, Howard C. ;
Pretorius, P. Hendrik ;
Smyczynski, Mark ;
Licho, Robert ;
Schneider, Peter ;
Farncombe, Troy ;
King, Michael A. .
MEDICAL PHYSICS, 2008, 35 (11) :4808-4815
[23]   Improving lesion localisation at colonoscopy: an analysis of influencing factors [J].
Adam S. Bryce ;
Mark S. Johnstone ;
S. J. Moug .
International Journal of Colorectal Disease, 2015, 30 :111-118
[24]   Analysis of influencing factors of boar claw lesion and lameness [J].
Wang, Chao ;
Li, Jia-Lian ;
Wei, Hong-Kui ;
Zhou, Yuan-Fei ;
Tan, Jia-Jian ;
Sun, Hai-Qing ;
Jiang, Si-Wen ;
Peng, Jian .
ANIMAL SCIENCE JOURNAL, 2018, 89 (05) :802-809
[25]   INVITRO CARIES - FACTORS INFLUENCING THE SHAPE OF THE DEVELOPING LESION [J].
WACHTEL, LW ;
BROWN, LR .
ARCHIVES OF ORAL BIOLOGY, 1963, 8 (02) :99-&
[26]   Improving lesion localisation at colonoscopy: an analysis of influencing factors [J].
Bryce, Adam S. ;
Johnstone, Mark S. ;
Moug, S. J. .
INTERNATIONAL JOURNAL OF COLORECTAL DISEASE, 2015, 30 (01) :111-118
[27]   Deep Learning for Lung Lesion Detection [J].
Isin, Ali ;
Sharif, Tazeen .
13TH INTERNATIONAL CONFERENCE ON THEORY AND APPLICATION OF FUZZY SYSTEMS AND SOFT COMPUTING - ICAFS-2018, 2019, 896 :799-806
[28]   Application of CT attenuation correction on lesion detection in SPECT imaging [J].
Birchall, J. D. ;
Blackwell, K. R. ;
Ganatra, R. H. ;
Griffith, K. ;
Perkins, A. C. ;
Smith, R. M. .
EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING, 2006, 33 :S318-S318
[29]   Lesion Border Detection in Buruli Ulcer Images [J].
Hu, Rui ;
Queen, Courtney M. ;
Zouridakis, George .
2012 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC), 2012, :5380-5383
[30]   Computerized lesion detection on breast MR images [J].
Bian, J. ;
Chen, W. ;
Newstead, G. ;
Giger, M. .
MEDICAL PHYSICS, 2006, 33 (06) :2195-2195