261 related articles for article (PubMed ID: 15487741)
1. Automatic detection and classification of hypodense hepatic lesions on contrast-enhanced venous-phase CT.
Bilello M; Gokturk SB; Desser T; Napel S; Jeffrey RB; Beaulieu CF
Med Phys; 2004 Sep; 31(9):2584-93. PubMed ID: 15487741
[TBL] [Abstract][Full Text] [Related]
2. Diagnosis of hepatic tumors with texture analysis in nonenhanced computed tomography images.
Huang YL; Chen JH; Shen WC
Acad Radiol; 2006 Jun; 13(6):713-20. PubMed ID: 16679273
[TBL] [Abstract][Full Text] [Related]
3. A retrieval-based computer-aided diagnosis system for the characterization of liver lesions in CT scans.
Dankerl P; Cavallaro A; Tsymbal A; Costa MJ; Suehling M; Janka R; Uder M; Hammon M
Acad Radiol; 2013 Dec; 20(12):1526-34. PubMed ID: 24200479
[TBL] [Abstract][Full Text] [Related]
4. Shape-constraint region growing for delineation of hepatic metastases on contrast-enhanced computed tomograph scans.
Zhao B; Schwartz LH; Jiang L; Colville J; Moskowitz C; Wang L; Leftowitz R; Liu F; Kalaigian J
Invest Radiol; 2006 Oct; 41(10):753-62. PubMed ID: 16971799
[TBL] [Abstract][Full Text] [Related]
5. A new fully automatic and robust algorithm for fast segmentation of liver tissue and tumors from CT scans.
Massoptier L; Casciaro S
Eur Radiol; 2008 Aug; 18(8):1658-65. PubMed ID: 18369633
[TBL] [Abstract][Full Text] [Related]
6. Preliminary data using computed tomography texture analysis for the classification of hypervascular liver lesions: generation of a predictive model on the basis of quantitative spatial frequency measurements--a work in progress.
Raman SP; Schroeder JL; Huang P; Chen Y; Coquia SF; Kawamoto S; Fishman EK
J Comput Assist Tomogr; 2015; 39(3):383-95. PubMed ID: 25700222
[TBL] [Abstract][Full Text] [Related]
7. Semiautomatic segmentation of liver metastases on volumetric CT images.
Yan J; Schwartz LH; Zhao B
Med Phys; 2015 Nov; 42(11):6283-93. PubMed ID: 26520721
[TBL] [Abstract][Full Text] [Related]
8. Computer aided detection of clusters of microcalcifications on full field digital mammograms.
Ge J; Sahiner B; Hadjiiski LM; Chan HP; Wei J; Helvie MA; Zhou C
Med Phys; 2006 Aug; 33(8):2975-88. PubMed ID: 16964876
[TBL] [Abstract][Full Text] [Related]
9. Distinction between cavernous hemangiomas of the liver and hepatic metastases on CT: value of contrast enhancement patterns.
Leslie DF; Johnson CD; Johnson CM; Ilstrup DM; Harmsen WS
AJR Am J Roentgenol; 1995 Mar; 164(3):625-9. PubMed ID: 7863883
[TBL] [Abstract][Full Text] [Related]
10. Automated knowledge-based detection of nonobstructive and obstructive arterial lesions from coronary CT angiography.
Kang D; Slomka PJ; Nakazato R; Arsanjani R; Cheng VY; Min JK; Li D; Berman DS; Kuo CC; Dey D
Med Phys; 2013 Apr; 40(4):041912. PubMed ID: 23556906
[TBL] [Abstract][Full Text] [Related]
11. Semi-automatic level set segmentation of liver tumors combining a spiral-scanning technique with supervised fuzzy pixel classification.
Smeets D; Loeckx D; Stijnen B; De Dobbelaer B; Vandermeulen D; Suetens P
Med Image Anal; 2010 Feb; 14(1):13-20. PubMed ID: 19828356
[TBL] [Abstract][Full Text] [Related]
12. Pulmonary nodule detection in CT images with quantized convergence index filter.
Matsumoto S; Kundel HL; Gee JC; Gefter WB; Hatabu H
Med Image Anal; 2006 Jun; 10(3):343-52. PubMed ID: 16542867
[TBL] [Abstract][Full Text] [Related]
13. A method to test the reproducibility and to improve performance of computer-aided detection schemes for digitized mammograms.
Zheng B; Gur D; Good WF; Hardesty LA
Med Phys; 2004 Nov; 31(11):2964-72. PubMed ID: 15587648
[TBL] [Abstract][Full Text] [Related]
14. Focal liver tumors: characterization with 3D perflubutane microbubble contrast agent-enhanced US versus 3D contrast-enhanced multidetector CT.
Luo W; Numata K; Morimoto M; Kondo M; Takebayashi S; Okada M; Morita S; Tanaka K
Radiology; 2009 Apr; 251(1):287-95. PubMed ID: 19221060
[TBL] [Abstract][Full Text] [Related]
15. Computer-aided diagnosis of focal liver lesions by use of physicians' subjective classification of echogenic patterns in baseline and contrast-enhanced ultrasonography.
Sugimoto K; Shiraishi J; Moriyasu F; Doi K
Acad Radiol; 2009 Apr; 16(4):401-11. PubMed ID: 19268851
[TBL] [Abstract][Full Text] [Related]
16. Automated detection of lung nodules in CT images using shape-based genetic algorithm.
Dehmeshki J; Ye X; Lin X; Valdivieso M; Amin H
Comput Med Imaging Graph; 2007 Sep; 31(6):408-17. PubMed ID: 17524617
[TBL] [Abstract][Full Text] [Related]
17. Automatic segmentation of the liver from multi- and single-phase contrast-enhanced CT images.
Ruskó L; Bekes G; Fidrich M
Med Image Anal; 2009 Dec; 13(6):871-82. PubMed ID: 19692288
[TBL] [Abstract][Full Text] [Related]
18. A computer-aided diagnostic system to characterize CT focal liver lesions: design and optimization of a neural network classifier.
Gletsos M; Mougiakakou SG; Matsopoulos GK; Nikita KS; Nikita AS; Kelekis D
IEEE Trans Inf Technol Biomed; 2003 Sep; 7(3):153-62. PubMed ID: 14518728
[TBL] [Abstract][Full Text] [Related]
19. Single-pass CT of hepatic tumors: value of globular enhancement in distinguishing hemangiomas from hypervascular metastases.
Leslie DF; Johnson CD; MacCarty RL; Ward EM; Ilstrup DM; Harmsen WS
AJR Am J Roentgenol; 1995 Dec; 165(6):1403-6. PubMed ID: 7484574
[TBL] [Abstract][Full Text] [Related]
20. Measurement of mesothelioma on thoracic CT scans: a comparison of manual and computer-assisted techniques.
Armato SG; Oxnard GR; MacMahon H; Vogelzang NJ; Kindler HL; Kocherginsky M; Starkey A
Med Phys; 2004 May; 31(5):1105-15. PubMed ID: 15191298
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
