Breast Masses Detection and Segmentation in Full-Field Digital Mammograms using Unified Convolution Neural Network.

Breast Cancer has been the primary reason for mortality in women of age between twenties and sixties worldwide; moreover early detection and treatment provides patients to get absolute treatment and decrease the mortality rate. Furthermore, recent research indicates that most experienced physicians have plenty of limitations, hence the plethora of work has been carried out to develop an automated mechanism of segmentation and classification of affected area and type of cancer; however, it is still considered to be highly challenging due to the variability of tumor in shape, low signal to noise ratio, shape, size and location of tumor. Furthermore, mammographic mass segmentation and detection are performed as a separate task and a convolution neural network is a highly adopted architecture for the same.

A Novel Approach towards Early Detection of Obliteration in Lumbar Lordosis.

The millennial age group (18 to 30 years) spend at least 6 hours sitting, either in college or at their workspace. High screen time as a routine, is the major cause for numerous spinal problems. Despite the wide research carried out on postural abnormalities, there exists numerous unrequited queries with regards to lumbar lordosis estimations, due to indeterminate parameters such as age, gender, lifestyle and diet.