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  • br However currently radiologists use single view

    2020-08-18

    113
    However, currently radiologists use single view CAD article. 114
    51 systems as a second reader for breast cancer diagnosis using
    52 FFDM images [10]. These CAD systems have high false positive 2. Literature survey
    53 (FP) and false negative (FN) rates because of varying subtle
    54 nature of abnormalities and limitations of imaging system
    55 [5,11]. The single view CAD systems for mass detection have To overcome the limitations of prompting single view CAD 116
    56 good diagnostic accuracy but less positive predictive value; systems, many researchers have attempted to develop multi- 117
    57 and hence are not as accurate and reliable as like the view-based CAD systems. The clinical studies on breast cancer 118
    58 experienced radiologist [12]. have indicated that two view mammograms help in achieving 119
    59 Some findings reveal that the sensitivity of digital mam- more diagnostic accuracy than with one view [18]. In their 120
    60 mography to detect breast lesions obscured by surrounding pioneer research, Good et al. [19] demonstrated that the 121
    61 and overlapping dense parenchymal GW311616 is as low as 30– multiview features of a single physical lesion on ipsilateral 122
    63 breast lesions during screening using mammography [14]. The 0.03 on ROC curves. This approach has limitations on 124
    64 diagnosis of these nonpalpable lesions is confirmed after the number of features and number of lesion pairs. Chang et al. 125
    65 histopathological reports (HPRs) of the sample tissues [20] investigated arc method with Az = 0.79 and Cartesian 126
    66 obtained using surgical or needle biopsy. However, the straight-line method with Az = 0.78 to localize and match 127
    67 patients as well as radiologists wish to avoid biopsy of benign breast lesions on 571 CC views with lesions on 571 MLO views. 128
    68 mass but without missing an opportunity to detect the In this scheme, the measurements related to nipple location 129
    69 malignant tumour. Thus, accurate detection and characteri- and chest wall orientation were not automatic. Paquerault 130
    70 zation of the suspicious lesions can help to minimize the et al. [21] developed two-view detection technique and 131
    71 degree of cosmetic disfigurement of the breast during reduced FP rate from 2.1 FPs/I to 1.2 FPs/I with sensitivity of 132
    72 treatment. In short, improvement in the detection perfor- 80%. Sahiner et al. [22] devised a new method combining 133
    Please cite predatory release article in press as: Sapate S, et al. Breast cancer diagnosis using abnormalities on ipsilateral views of digital mammograms. Biocybern Biomed Eng (2019), https://doi.org/10.1016/j.bbe.2019.04.008
    134 results of single view and two views analysis to reduce the
    3. Clinical dataset
    136 for the overall detection of breast cancer. The only drawback
    137 of these approaches is that a true mass may be missed when The clinical data for this study is taken from Tata Memorial 195
    138 the detected lesion is on either view and not on both views. Centre (TMC), Mumbai, India. Institutional Research Ethics 196
    139 Paquerault et al. [9] incorporated the geometric locations, Committee of TMC, Mumbai has approved the usage of all the 197
    140 textural and morphological features to correlate the suspi- biopsy-proven mammograms of breast cancer patients. The 198
    141 cious lesions detected on ipsilateral views for improving performance of the proposed two views CAD scheme is tested 199
    142 CAD performance. They improved the case-based detection on 110 pairs of CC and MLO views of FFDM obtained from 110 200
    144 information. However, the annular search region with 80 identity of all the patients prior to start the work. All the 202
    145 pixel radial width is a problem for smaller breasts. The images selected for this study have proper visible border and 203
    146 nipple detection is manual and not automatic as required the nipple is also in the breast profile. FFDM images cover 204
    147 for a CAD. Engeland et al. [23] presented a method to find patients with different densities of breasts belonging to all 205
    148 corresponding suspicious lesions on CC and MLO view with classes with respect to Breast Imaging Reporting and data 206
    150 one correspondence link of TP lesion with FP lesion instead (176 lesions) are malignant tumours and 22 (44 lesions) are 208
    151 of actual TP lesion. A new multiview-based CAD system