Today's modern medical imaging research faces the challenge of detecting brain tumor
through Magnetic Resonance Images (MRI). Normally, to produce images of soft tissue of …

Manual identification of brain tumors in Magnetic Resonance (MR) images is laborious, time-
consuming, and human error-prone. Automatic segmentation of brain tumors from MR …

In this work a new method for brain tumor detection is developed. For this purpose
watershed method is used in combination with edge detection operation. It is a color based …

Imaging plays a central role in the diagnosis and treatment planning of brain tumor. An
accurate segmentation is critical, especially when the tumor morphological changes remain …

Brain tumor is one of the most rigorous diseases in the medical science. An effective and
efficient analysis is always a key concern for the radiologists in the premature phase of …

Abstract− An accurate and standard techniques for breast tumor segmentation plays a
pivotal role in detecting and quantifying breast cancers. Segmentation of breast tumor in …

In this work, authors developed detection system for plant-disease using convolution neural
network (CNN) model. The developed system was trained using healthy and unhealthy …

Lung cancer is a lung-affecting chronic disease that may severely affects the respiratory
system. These days, lung cancer is known as the leading causes of death and is very difficult …

An Integration of image processing and soft computing techniques for the image analysis
plays a significant contribution in the field of image processing. One of the important class of …

Brain tumor is one of the most life-threatening diseases in the field of medical science. A
proper diagnosis of such a disease is required in its early phase of its generation. Various …