Abstract Brain tumor occurs owing to uncontrolled and rapid growth of cells. If not treated at an initial phase, it may lead death. Despite many significant efforts promising outcomes in this domain, accurate segmentation classification remain a challenging task. A major challenge for brain detection arises from the variations location, shape, size. The objective survey is deliver comprehensive...

Recent advances in artificial intelligence have greatly impacted the field of medical imaging and vastly improved development computational algorithms for data analysis. In pediatric neuro-oncology, radiomics, process obtaining high-dimensional from radiographic images, has been recently utilized applications including survival prognostication, molecular classification, tumor type classificatio...

Ovarian sex cord-stromal tumors are infrequent and represent approximately 7% of all primary ovarian tumors. This histopathologic ovarian tumor group differs considerably from the more prevalent epithelial ovarian tumors. Although sex cord-stromal tumors present in a broad age group, the majority tend to present as a low-grade disease that usually follows a nonaggressive clinical course in youn...

<span lang="EN-US">Deep learning (DL) is a subfield of artificial intelligence (AI) used in several sectors, such as cybersecurity, finance, marketing, automated vehicles, and medicine. Due to the advancement computer performance, DL has become very successful. In recent years, it processed large amounts data, achieved good results, especially image analysis segmentation classification. M...

background : labeling, gathering mutual information, clustering and classification of central nervous system tumors may assist in predicting not only distinct diagnoses based on tumor-specific features but also prognosis. this study evaluates the epidemi- ological features of central nervous system tumors in children who referred to mahak’s pediatric cancer treatment and research center in tehr...

World Health Organization (WHO) published an updated article regarding the classification of tumors of the brain. In this updated classification, brains tumors are not only classified based on their histology but molecular parameters are also incorporated in its classification. In this manuscript, we primarily focus on astrocytoma, meningioma, metastatic tumors, and pituitary tumors, providing ...

Tumor classification is a well-studied problem in the field of bioinformatics. Developments in the field of DNA chip design have now made it possible to measure the expression levels of thousands of genes in sample tissue from healthy cell lines or tumors. A number of studies have examined the problems of tumor classification: class discovery, the problem of defining a number of classes of tumo...

The classification of thymic epithelial neoplasms has been a controversial topic for many years. Recent advances in diagnostic methods and renewed interest in the biology of these tumors has led to efforts by investigators to shed new light on their biologic behavior and to offer novel perspectives on these unusual neoplasms. Several new classification schemes have been proposed, including the ...

Background: Rhabdomyosarcoma is a rare malignant soft tissue sarcoma and the most common sarcoma of childhood. The purpose of this study was to investigate the distribution of age and sex of patients, pathological subtypes and to determine the role of staging and classification of RMS on treatment outcome. Materials and Methods: This retrospective study included patients who diagnosed with RMS ...

Brain cancer is a critical disease that results in the deaths of many individuals. Early detection and classification brain tumors essential for effective treatment improved patient outcomes. However, current manual examination MRI images tumor can be time-consuming imprecise. In this project, we propose computer-based system utilizes image processing techniques convolutional neural networks (C...