TY - GEN
T1 - Parallel realization of cognitive cells on film mammography
AU - James, Alex Pappachen
AU - Sugathan, Sherin
PY - 2013
Y1 - 2013
N2 - High speed detection of breast masses from mammography images at an affordable cost is a problem of practical significance in large volume real-time processing and diagnostic assessments. In this paper, we present a new approach to real-time detection of breast masses by introducing the concept of cognitive cells that has a fully parallel high speed computing architecture realised in a low cost hardware. The prototype system was tested using the Compute Unified Device Architecture (CUDA) that achieved an average speed of 6 ms for processing a single 1024x1024 pixels mammography image. Initial results shows feasibility of using cognitive cells for suspicious breast cancer mass detection in mammograms with superior performances in speed in comparison to other standard methods. We report specificity of 95.25% and the cancer false positives per image as 2.275 for MISC, ASYM, CIRC and SPIC cases, while a relatively lower specificity of 70% and the false positives per image as 2.25 is reported for CALC and ARCH cases of abnormalities.
AB - High speed detection of breast masses from mammography images at an affordable cost is a problem of practical significance in large volume real-time processing and diagnostic assessments. In this paper, we present a new approach to real-time detection of breast masses by introducing the concept of cognitive cells that has a fully parallel high speed computing architecture realised in a low cost hardware. The prototype system was tested using the Compute Unified Device Architecture (CUDA) that achieved an average speed of 6 ms for processing a single 1024x1024 pixels mammography image. Initial results shows feasibility of using cognitive cells for suspicious breast cancer mass detection in mammograms with superior performances in speed in comparison to other standard methods. We report specificity of 95.25% and the cancer false positives per image as 2.275 for MISC, ASYM, CIRC and SPIC cases, while a relatively lower specificity of 70% and the false positives per image as 2.25 is reported for CALC and ARCH cases of abnormalities.
KW - Breast Cancer
KW - CUDA
KW - Cognitive Cell
KW - Film Mammography
KW - Parallel Computing Networks
UR - http://www.scopus.com/inward/record.url?scp=84893504072&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84893504072&partnerID=8YFLogxK
U2 - 10.1109/TrustCom.2013.232
DO - 10.1109/TrustCom.2013.232
M3 - Conference contribution
AN - SCOPUS:84893504072
SN - 9780769550220
T3 - Proceedings - 12th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2013
SP - 1873
EP - 1878
BT - Proceedings - 12th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2013
T2 - 12th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2013
Y2 - 16 July 2013 through 18 July 2013
ER -