Introduction The domestic dog, Canis familiaris , is quickly gaining traction as an advantageous model for use in the study of cancer, one leading causes death worldwide. Naturally occurring canine cancers share clinical, histological, and molecular characteristics with corresponding human diseases. Methods In this study, we take a deep-learning approach to test how similar gene expression prof...

In recent years, brain tumors become the leading cause of death in the world. Detection and rapid classification of this tumor are very important and may indicate the likely diagnosis and treatment strategy. In this paper, we propose deep learning techniques based on the combinations of pre-trained VGG-16 CNNs to classify three types of brain tumors (i.e., meningioma, glioma, and pituitary tumo...

Background: Neurofollicular hamartoma (NFH) is characterized histopathologically by fascicles of spindle cells that laterally delimited by hyperplastic folliculosebaceous units. It usually appears on face, near the nose or nasolabial fold. It does not manifest true neural differentiation and recently the term spindle cell predominant trichodiscoma (SCPT) has been used instead. Case Presentatio...

Lung cancer is the second most prevalent type of cancer. Early detection and classification of lung tumors helps in better survival. The paper presents a computer aided diagnosis (CAD) system for chest computed tomography (CT) images that focus on a new algorithm to classify lung tumor into benign or malignant using advanced neural network based classifier. Statistical textural features are ext...

INTRODUCTION: Automatic segmentation and classification of brain tumors help in improvement treatment which will increase the life patient. Tumor may be noncancerous (benign) or cancerous (malignant). Precancerous cells also form into cancer.OBJECTIVES: Hough CNN is applied for selected section applies hough casting technique segmentation. METHODS: A multistage methodof extracting features, wit...