Automatic segmentation of brain tumour is the process of separating abnormal tissues from
normal tissues, such as white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) …

Over the past decades, food quality and safety have seriously been disturbing public health.
Traditional monitoring methods of food-quality evaluation have been time consuming and …

There is a need for robust, fully automated whole body organ segmentation for diagnostic
CT. This study investigates and optimizes a Random Forest algorithm for automated organ …

A computer software system is designed for segmentation and classification of benign and
malignant tumour slices in brain computed tomography images. In this study, the authors …

Computed tomography (CT) images are commonly used to diagnose liver disease. It is
sometimes very difficult to comment on the type, category and level of the tumor, even for …

The brain tumor is a cluster of the abnormal tissues, and it is essential to categorize brain
tumors for treatment using Magnetic Resonance Imaging (MRI). The segmentation of tumors …

Uncontrolled and fast cell proliferation is the cause of brain tumors. Early cancer detection is
vitally important to save many lives. Brain tumors can be divided into several categories …

Automatic detection of brain tumor is a difficult task due to variations in type, size, location
and shape of tumors. In this paper, a multi-modality framework for automatic tumor detection …

Classification of brain neoplasm images is one of the most challenging research areas in the
field of medical image processing. The main objective of this study is to design a brain …

Segmentation methods are so much efficient to segment complex tumor from challenging
datasets. MACCAI BRATS 2013-2017 brain tumor dataset (FLAIR, T2) had been taken for …