Mammogram breast cancer images have the ability to assist physicians in detecting disease caused by cells normal growth. Developing algorithms and software to analyze these images may also assist physicians in there daily work. This study that shows the outcome of applying image processing threshold, ...
Primarily it allows the search for abnormalities to be limited to the region of the breast tissue without undue influence from the background of the mammogram. The presence of pectoral muscle in mammograms biases detection procedures, which recommends removing the pectoral muscle during mammogram image...
study, normal and abnormal breast image used as the standard input are taken from Mammographic Image Analysis Society (MIAS) digital mammogram database. Th... M Pratiwi,Alexander,J Harefa,... - 《Procedia Computer Science》 被引量: 15发表: 2015年 Breast Lesions Classification applied to a ref...
(2006). A new approach to the classification of mammographic masses and normal breast tissue. In 18th International conference on pattern recognition, 2006. ICPR 2006 (pp. 707–710). IEEE. https://doi.org/10.1109/icpr.2006.113. Vadivel, A., & Surendiran, B. (2013). A fuzzy rule-based...
Non-small cell lung cancer (NSCLC), the most common type of lung cancer, is one of serious diseases causing death for both men and women. Computer-aided diagnosis and survival prediction of NSCLC, is of great importance in providing assistance to diagnos
Sahiner B, Heang-Ping Chan, Petrick N, Datong Wei, Helvie MA, Adler DD, Goodsitt MM (1996) Classification of mass and normal breast tissue: a convolution neural network classifier with spatial domain and texture images. IEEE Trans Med Imaging 15(5):598–610. https://doi.org/10.1109/42....
Recently, renewed interest in thermography has been created because of the availability of highly sensitive infrared cameras and a greater understanding of advanced image processing techniques and computer modeling. The normal breast tissue has a predictable emanation of heat patterns on the skin surface...
Deep learning has been widely used for medical image segmentation and a large number of papers has been presented recording the success of deep learning in the field. A comprehensive thematic survey on medical image segmentation using deep learning techniques is presented. This paper makes two origin...
unrestricted data-access programme was extended to all researchers worldwide. ADNI’s original aim was to employ 800 people aged 55 to 90 years to enroll in the analysis of approximately 200 cognitively normal elderly individuals to be pursued for 3 years, 400 individuals to be followed for 3 ...
Sahiner B, Chan H-P, Petrick N, Wei D, Helvie MA, Adler DD et al (1996) Classification of mass and normal breast tissue: a convolution neural network classifier with spatial domain and texture images. IEEE Trans Med Imaging 15:598–610 ...