Detecting Breast Arterial Calcifications in Mammograms with Transfer Learning

Enhancement of Micro Calcifications in Mammograms

Mammogram enhancement is required as an early step to detect the breast cancer. Since the calcification area is dark and images have low contrast, it results in difficulty in image enhancement. Various techniques have been developed till date based upon multi-scale morphology and wavelet transformations. Herein, a new enhancement algorithm has been developed based upon multi-scale morphology. T...

Arterial calcifications

Arterial calcifications as found with various imaging techniques, like plain X-ray, computed tomography or ultrasound are associated with increased cardiovascular risk. The prevalence of arterial calcification increases with age and is stimulated by several common cardiovascular risk factors. In this review, the clinical importance of arterial calcification and the currently known proteins invo...

Detection of calcifications in digitized mammograms using wavelet packet analysis

Volume Reconstruction of Clustered Micro-Calcifications in Mammograms

Breast cancer is one of the leading causes for death of women in the western world. Detection of anomalies early pathological stages and immidiate treatment are essential for successful cure. Early stages of breast cancer are indicated by the occurance of microcalcifications [2]. About 30% of all tissue changes show clustered microcalcifications. Their shape and spatial arrangement are of high ...

Resolution effects on the morphology of calcifications in digital mammograms

The development of computer assisted diagnosis (CAD) techniques and direct digital mammography systems have generated significant interest in the issue of the effect of image resolution on the detection and classification (benign vs malignant) of mammographic abnormalities. CAD in particular seems to heavily depend on image resolution, either due to the inherent algorithm design and optimizatio...