title: Extraction of medically interpretable features for classification of malignancy in breast thermography.
abstract: Thermography, with high-resolution cameras, is being re-investigated as a possible breast cancer screening imaging modality, as it does not have the harmful radiation effects of mammography. This paper focuses on automatic extraction of medically interpretable non-vascular thermal features. We design these features to differentiate malignancy from different non-malignancy conditions, including hormone sensitive tissues and certain benign conditions, which have an increased thermal response. These features increase the specificity for breast cancer screening, which had been a long known problem in thermographic screening, while retaining high sensitivity. These features are also agnostic to different cameras and resolutions (up to an extent). On a dataset of around 78 subjects with cancer and 187 subjects without cancer, that have some benign diseases and conditions with thermal responses, we are able to get around 99% specificity while having 100% sensitivity. This indicates a potential break-through in thermographic screening for breast cancer. This shows promise for undertaking a comparison to mammography with larger numbers of subjects with more data variations.
authors.forename: Himanshu
authors.initials: H
authors.lastname: Madhu
authors.forename: Siva Teja
authors.initials: ST
authors.lastname: Kakileti
authors.forename: Krithika
authors.initials: K
authors.lastname: Venkataramani
authors.forename: Susmija
authors.initials: S
authors.lastname: Jabbireddy
mesh_terms: D001940:Breast / Q000473:pathology; D001943:Breast Neoplasms / Q000175:diagnosis*; D006801:Humans; D008327:Mammography; D012680:Sensitivity and Specificity; D013817:Thermography