Copyright © 2006 Siemens Medical Solutions USA, Inc. All rights reserved. Learning-based Component for Suppression of Rectal Tube False Positives: Evaluation.

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Copyright © 2006 Siemens Medical Solutions USA, Inc. All rights reserved. Learning-based Component for Suppression of Rectal Tube False Positives: Evaluation of Performance on 780 CTC Cases S Lakare, A Barbu, M Dundar, M Wolf, L Bogoni, D Comaniciu Computer-Aided Detection and Knowledge Solutions Siemens Medical Solutions USA, Inc.

Copyright © 2006 Siemens Medical Solutions USA, Inc. All rights reserved. Page 2 Motivation  Removing CAD marks on Rectal Tubes can decrease reviewing time spent on obvious false positives  Fewer obvious false positive marks can increase radiologists’ confidence of the CAD system

Copyright © 2006 Siemens Medical Solutions USA, Inc. All rights reserved. Page 3 Marks on Rectal Tubes  Rectal tubes can have a bumpy, polyp-like shape  A CAD system can detect those bumps – resulting in false-positives (FPs)

Copyright © 2006 Siemens Medical Solutions USA, Inc. All rights reserved. Page 4 Overview – Rectal Tube Detection Module 3D circles Short tubes Segmented tube Input volumeOutput

Copyright © 2006 Siemens Medical Solutions USA, Inc. All rights reserved. Page 5 3D Circle Detection  3D curvature, gradient and data based features  12 circles (4 radii x 3 relative positions) relative to the circle of interest  8 types of statistics (mean, variance, percentiles, etc)  in total 6720 features  15,000 positive samples  207,000 negative samples  Detection Rate: 95.6%

Copyright © 2006 Siemens Medical Solutions USA, Inc. All rights reserved. Page 6 Short Tube Detection  Short tubes are constructed from pairs of 3D circles of well aligned tubes  13,700 positive samples  400,000 negative samples  Detection Rate: 95.1%  The tubes are then connected by dynamic programming The parameters of a short tube A short tube is constructed from a pair of 3D circles

Copyright © 2006 Siemens Medical Solutions USA, Inc. All rights reserved. Page 7 Training Data  Cases with clean prep  234 volumes  8 sites  Siemens, GE, Toshiba MDCT  4, 16 and 64 slice scanners  Cases with tagged prep (combinations of iodine & barium)  154 volumes  4 sites  Siemens and GE MDCT  16 and 64 slice scanners  Rectal Tubes are annotated and then used for training

Copyright © 2006 Siemens Medical Solutions USA, Inc. All rights reserved. Page 8 Results – Standalone System  Tested on 210 unseen cases  Detection Rate: 94.7%  26 false positives  0.12 FP/vol  Running time was 5.3 seconds/volume  None of the 26 false alarms was a polyp

Copyright © 2006 Siemens Medical Solutions USA, Inc. All rights reserved. Page 9 Detection Results

Copyright © 2006 Siemens Medical Solutions USA, Inc. All rights reserved. Page 10 False Positives

Copyright © 2006 Siemens Medical Solutions USA, Inc. All rights reserved. Page 11 Integration into CAD Prototype* Input Data Candidate Generation Feature Computation ClassificationCAD marks * Work in Progress, not available commercially

Copyright © 2006 Siemens Medical Solutions USA, Inc. All rights reserved. Page 12 Integration into CAD Prototype Input Data Candidate Generation Feature Computation Classification CAD marksRectal Tube Detection

Copyright © 2006 Siemens Medical Solutions USA, Inc. All rights reserved. Page 13 Test Data  Cases with clean prep  405 cases, 783 volumes  10 sites  Siemens, GE, Toshiba MDCT  4, 16 and 64 slice scanners  Cases with tagged prep (combinations of iodine & barium)  373 cases, 587 volumes  4 sites  Siemens and GE MDCT  16 and 64 slice scanners

Copyright © 2006 Siemens Medical Solutions USA, Inc. All rights reserved. Page 14 Integrated Results – CG Stage Input Data Candidate Generation CAD marksRectal Tube Detection

Copyright © 2006 Siemens Medical Solutions USA, Inc. All rights reserved. Page 15 Integrated Results – CG Stage  Clean cases  257/405 had candidates on rectal tube (351/783 volumes)  Candidates/patient count reduced by 2.92  Candidates/volume count reduced by 2.04  Tagged cases  All volumes had candidates on rectal tube  Candidates/patient count reduced by 2.56  Candidates/volume count reduced by 1.70

Copyright © 2006 Siemens Medical Solutions USA, Inc. All rights reserved. Page 16 Integrated Results – Overall Input Data Candidate Generation Feature Computation Classification CAD marksRectal Tube Detection

Copyright © 2006 Siemens Medical Solutions USA, Inc. All rights reserved. Page 17 Integrated Results – Overall  Clean cases  Candidates/patient count reduced by 0.30 (8%)  Candidates/volume count reduced by 0.20 (10%)  Tagged cases  Candidates/patient count reduced by 0.15 (3%)  Candidates/volume count reduced by 0.09 (3%)

Copyright © 2006 Siemens Medical Solutions USA, Inc. All rights reserved. Page 18 Conclusion  Presented a Rectal Tube detection method  CAD marks on rectal tubes are suppressed  Reduction in false positives  Can potentially reduce interpretation time for Radiologists  The system does not miss any additional polyps