TY - GEN
T1 - Matching Tumour Candidate Points in Multiple Mammographic Views for Breast Cancer Detection
AU - Abdel-Nasser, Mohamed
AU - Moreno, Antonio
AU - Abdelwahab, Mohamed A.
AU - Saleh, Adel
AU - Abdulwahab, Saddam
AU - Singh, Vivek K.
AU - Puig, Domenec
N1 - Funding Information:
This research was partly supported by the Spanish Government through project DPI2016-77415-R.
Publisher Copyright:
© 2019 IEEE.
PY - 2019/2/20
Y1 - 2019/2/20
N2 - Matching candidate points from multiple mammographic views corresponding to the same patient may lead to an improvement in the accuracy of Computer Aided Diagnosis systems and it can help the radiologists to detect breast cancer in early stages, leading to a reduction of the percentage of mortality. In this paper, we propose a matching approach in order to detect correspondences between some candidate points from multiple mammographic views. Initially, a Scale Invariant Feature Transform detector is used to determine some candidate points in the mammographic views, then a combination between texture features is proposed to check the abnormality of the local region that surrounds each candidate point. The candidate points can be matched by integrating the information given by the texture analysis, the distance from the nipple and the location of the candidate points relative to the nipple. Some experiments are presented to show the effectiveness of the proposed approach.
AB - Matching candidate points from multiple mammographic views corresponding to the same patient may lead to an improvement in the accuracy of Computer Aided Diagnosis systems and it can help the radiologists to detect breast cancer in early stages, leading to a reduction of the percentage of mortality. In this paper, we propose a matching approach in order to detect correspondences between some candidate points from multiple mammographic views. Initially, a Scale Invariant Feature Transform detector is used to determine some candidate points in the mammographic views, then a combination between texture features is proposed to check the abnormality of the local region that surrounds each candidate point. The candidate points can be matched by integrating the information given by the texture analysis, the distance from the nipple and the location of the candidate points relative to the nipple. Some experiments are presented to show the effectiveness of the proposed approach.
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U2 - 10.1109/ITCE.2019.8646516
DO - 10.1109/ITCE.2019.8646516
M3 - Conference contribution
AN - SCOPUS:85063344408
T3 - Proceedings of 2019 International Conference on Innovative Trends in Computer Engineering, ITCE 2019
SP - 202
EP - 207
BT - Proceedings of 2019 International Conference on Innovative Trends in Computer Engineering, ITCE 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 International Conference on Innovative Trends in Computer Engineering, ITCE 2019
Y2 - 2 February 2019 through 4 February 2019
ER -
