Hence a simple and fast method was proposed for feature selection using Jacobi Moments with SVM classifier to distinguish between the normal and abnormal breast tissues and to classify tumors as malignant or benign. Experiments were performed on 192 mammograms from the Mammographic Image Analysis ...
- 《Journal of Medical Imaging》 被引量: 6发表: 2015年 Texture analysis of masses malignant in mammograms images using a combined approach of diversity index and local binary patterns distribution Gattass, "Texture analysis of masses malignant in mam- mograms images using a combined approach of ...
Having a baseline mammogram, regardless of the frequency of your mammograms, is helpful in establishing what normal looks like for you. Over time, a woman's breasts can change. This can happen after childbirth, following abreast biopsy, or with breast implants. It is not uncommon to getbenign...
The classifier is part of a Computer Aided Diagnosis (CADx) scheme that is aimed to assisting radiologists in making more accurate diagnoses of breast cancer on mammograms. The methods to be considered were; Support Vector Machine (SVM), Kernel Fisher Discriminated (KFD), Relevance Vector Machine...
Computerized mass detection in whole breast ultrasound images: reduction of false positives using bilateral subtraction technique The comparison of left and right mammograms is a common technique used by radiologists for the detection and diagnosis of masses. In mammography, computer-... Y Ikedo,ML ...
Improvements in mammographic acquisition techniques have resulted in making the early signs of breast cancer more apparent on mammograms. However, the accuracy of the overall mammographic examination depends on both the quality of the mammographic images and the ability of the radiologist to interpret th...
It has important research value for the further study of histopathological image classification of liver cancer [18,19,20]. In recent years, with the rapid development of artificial intelligence, artificial intelligence algorithms have been widely used in the medical field. Deep learning, as one of...
The advent of Deep Learning (DL) and Computer Vision techniques is widely used to perform breast cancer diagnosis. This paper presents a new Optimal Multi-Level Thresholding-based Segmentation with DL enabled Capsule Network (OMLTS-DLCN) breast cancer diagnosis model utilizing digital mammograms. ...
When you’re deciding how you want the procedure performed, you have two types of mammograms to choose from. The bilateral and 3D mammogram processes are nearly identical from the patient perspective. Both methods function on one breast at a time, compressing the tissue with a paddle to maximiz...
Women with high mammographic breast density have a four- to fivefold increased risk of developing breast cancer compared to women with fatty breasts. Many ... C Glide,N Duric,P Littrup - 《Medical Physics》 被引量: 136发表: 2007年 Segmentation of the fibro-glandular disc in mammograms using...