Name
Title | ||
|---|---|---|
Effect of massive training artificial neural networks for rib suppression on reduction of false positives in computerized detection of nodules on chest radiographs |
Abstract | ||
|---|---|---|
A major challenge in computer-aided diagnostic (CAD) schemes for nodule detection on chest radiographs is the detection of nodules that overlap with ribs. Our purpose was to develop a technique for false-positive reduction in a CAD scheme using a rib-suppression technique based on massive training artificial neural networks (MTANNs). We developed a multiple MTANN (multi-MTANN) consisting of eight MTANNs for removing eight types of false positives. For further removal of false positives caused by ribs, we developed a rib-suppression technique using a multi-resolution MTANN consisting, of three different resolution MTANNs. To suppress the contrast of ribs, the multi-resolution MTANN was trained with input chest radiographs and the teaching soft-tissue images obtained by using a dual-energy subtraction technique. Our database consisted of 91 nodules in 91 chest radiographs. With our original CAD scheme based on a difference image technique with linear discriminant analysis, a sensitivity of 82.4% (75/91 nodules) with 4.5 (410/91) false positives per image was achieved. The trained multi-MTANN was able to remove 62.7% (257/410) of false positives with a loss of one true positive. With the rib-suppression technique, the contrast of ribs in chest radiographs was suppressed substantially. Due to the effect of rib-suppression, 41.2% (63/153) of the remaining, false positives were removed without a loss of any true positives. Thus, the false-positive rate of our CAD scheme was improved substantially, while a high sensitivity was maintained. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1117/12.594730 | PROCEEDINGS OF THE SOCIETY OF PHOTO-OPTICAL INSTRUMENTATION ENGINEERS (SPIE) |
Keywords | Field | DocType |
computer-aided diagnosis,lung nodule,artificial neural network,chest radiograph,rib suppression,nodule detection,lung cancer screening | Chest radiograph,Lung cancer screening,Rib cage,Computer-aided diagnosis,Radiography,Radiology,Linear discriminant analysis,Subtraction,Medicine,False positive paradox | Conference |
Volume | ISSN | Citations |
5747 | 0277-786X | 3 |
PageRank | References | Authors |
0.45 | 0 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kenji Suzuki | 1 | 19 | 5.04 |
| Junji Shiraishi | 2 | 19 | 8.08 |
| Feng Li | 3 | 338 | 49.66 |
| Hiroyuki Abe | 4 | 44 | 5.81 |
| Heber MacMahon | 5 | 202 | 31.61 |
| Kunio Doi | 6 | 35 | 8.75 |