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Abraham H. Dachman to Colonic Polyps

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This is a "connection" page, showing publications Abraham H. Dachman has written about Colonic Polyps.
Abraham H. Dachman
Connection Strength
6.609
Colonic Polyps
  1. To Wait or to Act: How CT Colonography Can Improve Management of Colorectal Polyps. Radiology. 2024 Jan; 310(1):e232975.
    View in: PubMed
    Score: 0.877
  2. Structured reporting and quality control in CT colonography. Abdom Radiol (NY). 2018 03; 43(3):566-573.
    View in: PubMed
    Score: 0.585
  3. CT colonography with computer-aided detection: recognizing the causes of false-positive reader results. Radiographics. 2014 Nov-Dec; 34(7):1885-905.
    View in: PubMed
    Score: 0.464
  4. CAD-associated reader error in CT colonography. Acad Radiol. 2012 Jul; 19(7):801-10.
    View in: PubMed
    Score: 0.390
  5. Effect of computer-aided detection for CT colonography in a multireader, multicase trial. Radiology. 2010 Sep; 256(3):827-35.
    View in: PubMed
    Score: 0.346
  6. CT colonography: advanced computer-aided detection scheme utilizing MTANNs for detection of "missed" polyps in a multicenter clinical trial. Med Phys. 2010 Jan; 37(1):12-21.
    View in: PubMed
    Score: 0.332
  7. Comparison of polyp size and volume at CT colonography: implications for follow-up CT colonography. AJR Am J Roentgenol. 2009 Dec; 193(6):1561-7.
    View in: PubMed
    Score: 0.330
  8. Comparison of optical colonoscopy and CT colonography for polyp detection. AJR Am J Roentgenol. 2009 Nov; 193(5):1289-90.
    View in: PubMed
    Score: 0.328
  9. CT colonography: false-negative interpretations. Radiology. 2007 Jul; 244(1):165-73.
    View in: PubMed
    Score: 0.279
  10. CAD techniques, challenges, and controversies in computed tomographic colonography. Abdom Imaging. 2005 Jan-Feb; 30(1):26-41.
    View in: PubMed
    Score: 0.235
  11. The effect of reconstruction algorithm on conspicuity of polyps in CT colonography. AJR Am J Roentgenol. 2004 Nov; 183(5):1349-53.
    View in: PubMed
    Score: 0.232
  12. Quality and consistency in CT colonography and research reporting. Radiology. 2004 Feb; 230(2):319-23.
    View in: PubMed
    Score: 0.220
  13. Automated knowledge-guided segmentation of colonic walls for computerized detection of polyps in CT colonography. J Comput Assist Tomogr. 2002 Jul-Aug; 26(4):493-504.
    View in: PubMed
    Score: 0.198
  14. Diagnostic performance of virtual colonoscopy. Abdom Imaging. 2002 May-Jun; 27(3):260-7.
    View in: PubMed
    Score: 0.195
  15. Computerized detection of colonic polyps at CT colonography on the basis of volumetric features: pilot study. Radiology. 2002 Feb; 222(2):327-36.
    View in: PubMed
    Score: 0.192
  16. Automated segmentation of colonic walls for computerized detection of polyps in CT colonography. J Comput Assist Tomogr. 2001 Jul-Aug; 25(4):629-38.
    View in: PubMed
    Score: 0.184
  17. CT colonography with three-dimensional problem solving for detection of colonic polyps. AJR Am J Roentgenol. 1998 Oct; 171(4):989-95.
    View in: PubMed
    Score: 0.152
  18. Small simulated polyps in pig colon: sensitivity of CT virtual colography. Radiology. 1997 May; 203(2):427-30.
    View in: PubMed
    Score: 0.138
  19. CT colonography for the detection of nonpolypoid adenomas: sensitivity assessed with restricted national CT colonography trial criteria. AJR Am J Roentgenol. 2014 Dec; 203(6):W614-22.
    View in: PubMed
    Score: 0.117
  20. National CT colonography trial (ACRIN 6664): comparison of three full-laxative bowel preparations in more than 2500 average-risk patients. AJR Am J Roentgenol. 2011 May; 196(5):1076-82.
    View in: PubMed
    Score: 0.091
  21. Can radiologist training and testing ensure high performance in CT colonography? Lessons From the National CT Colonography Trial. AJR Am J Roentgenol. 2010 Jul; 195(1):117-25.
    View in: PubMed
    Score: 0.086
  22. CT colonography polyp matching: differences between experienced readers. Eur Radiol. 2009 Jul; 19(7):1723-30.
    View in: PubMed
    Score: 0.078
  23. Formative evaluation of standardized training for CT colonographic image interpretation by novice readers. Radiology. 2008 Oct; 249(1):167-77.
    View in: PubMed
    Score: 0.076
  24. Mixture of expert 3D massive-training ANNs for reduction of multiple types of false positives in CAD for detection of polyps in CT colonography. Med Phys. 2008 Feb; 35(2):694-703.
    View in: PubMed
    Score: 0.073
  25. The solitary colonic polyp: radiologic-histologic differentiation and significance. Radiology. 1986 Jul; 160(1):9-16.
    View in: PubMed
    Score: 0.065
  26. Characterization of normal ileocecal valve density on CT colonography. J Comput Assist Tomogr. 2006 Jan-Feb; 30(1):58-61.
    View in: PubMed
    Score: 0.063
  27. Region-based supine-prone correspondence for the reduction of false-positive CAD polyp candidates in CT colonography. Acad Radiol. 2005 Jun; 12(6):695-707.
    View in: PubMed
    Score: 0.060
  28. Computer-aided diagnosis for CT colonography. Semin Ultrasound CT MR. 2004 Oct; 25(5):419-31.
    View in: PubMed
    Score: 0.058
  29. Computer-aided diagnosis scheme for detection of polyps at CT colonography. Radiographics. 2002 Jul-Aug; 22(4):963-79.
    View in: PubMed
    Score: 0.049
  30. CT colonography: the next colon screening examination? Radiology. 2000 Aug; 216(2):331-41.
    View in: PubMed
    Score: 0.043
  31. Polypoid and pseudopolypoid manifestations of inflammatory bowel disease. Radiographics. 1991 Mar; 11(2):293-304.
    View in: PubMed
    Score: 0.023
  32. Accuracy of CT colonography for detection of large adenomas and cancers. N Engl J Med. 2008 Sep 18; 359(12):1207-17.
    View in: PubMed
    Score: 0.019
  33. Analysis of air contrast barium enema, computed tomographic colonography, and colonoscopy: prospective comparison. Lancet. 2005 Jan 22-28; 365(9456):305-11.
    View in: PubMed
    Score: 0.015
  34. Computerized tomographic colonography: performance evaluation in a retrospective multicenter setting. Gastroenterology. 2003 Sep; 125(3):688-95.
    View in: PubMed
    Score: 0.013
Connection Strength

The connection strength for concepts is the sum of the scores for each matching publication.

Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.