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This papers reports on methodologies and outcome of a study aiming at developing robust tool to evaluate and classify histology images of cervical cancer. Using the histology images acquired from the pathology laboratories in an Indonesian hospital, this study aims to classify cervical biopsy images based on four well known discriminatory features a) the ratio of nuclei to cytoplasm b) diameter of...
Breast cancer is the second leading cause of cancer deaths among women and micro calcifications clusters are one of the most important indicators of breast disease. A Computer-Aided Diagnosis algorithm has been developed to assist radiologists in the diagnosis of mammographic clusters. Classification performance was evaluated with the diagnosis algorithm, and the final result looks great.
Assessing the precision in the estimation of lesion dimensions is a prerequisite for the determination of growth rates and response to therapy both in clinical practice and research. An initial study was designed and performed to evaluate three different marking methods: uni-dimensional (maximum diameter of nodule in-axial plane), manual volumetric and a computer assisted mark-up (CAM) method. The...
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