Provisional Application No. The U. Government may have certain rights in this invention. In addition to breast self-examination BSE and clinical breast examination CBE --inspection and manual palpation of the breast which is performed by physicians and other medical caregivers-many imaging modalities are used to identify and evaluate breast lumps and tissues such as tumors, cysts, and other abnormalities "lesions" and to help differentiate benign noncancerous and malignant cancerous breast disease. Furthermore, abnormalities, when present, may be subtle and difficult for the examiner's fingers to distinguish from adjacent normal tissue.
Spatial variations in optical and physiological properties of healthy breast tissue. - CORE
Breast cancer research, 11 3. To date research into density has relied on a single measure for example, percent density PD summarising the average level of density for the whole breast, with no consideration of how the radiodense tissue may be distributed. The spatial autocorrelation Moran's I value of regional PD for each image was calculated to investigate spatial clustering of density, whether the degree of clustering varied between a woman's two breasts and whether it was affected by age and other known density correlates. High-density areas tended to cluster in the central regions of the breast, regardless of the level of overall PD, but with considerable between-woman variability in regional PD. Neither parity nor age at first birth affected the level of spatial autocorrelation of density, but increasing body mass index BMI was associated with a decrease in the degree of spatial clustering. The degree of clustering was similar within a woman's two breasts and between women, and was little affected by age or reproductive factors although it declined with increasing BMI. The spatial distribution of radiodense breast tissue: a longitudinal study.
Differential spatial expression and activation pattern of EGFR and HER2 in human breast cancer
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Breast cancer screening provides sensitive tumor identification, but low specificity implies that a vast majority of biopsies are not ultimately diagnosed as cancer. Automated techniques to evaluate biopsies can prevent errors, reduce pathologist workload and provide objective analysis. Fourier transform infrared FT-IR spectroscopic imaging provides both molecular signatures and spatial information that may be applicable for pathology. Here, we utilize both the spectral and spatial information to develop a combined classifier that provides rapid tissue assessment.