AI Medical Compendium Topic:
Brain Neoplasms

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Use of artificial neural networks to predict the probability of developing new cerebral metastases after radiosurgery alone.

Journal of neurosurgical sciences
BACKGROUND: The present study aimed to predict the probability of developing new cerebral metastases after Gamma Knife radiosurgery (GKR) alone in patients with 1-3 brain metastases by artificial neural network (ANN) model.

Diagnosis of Brain Metastases from Lung Cancer Using a Modified Electromagnetism like Mechanism Algorithm.

Journal of medical systems
Brain metastases are commonly found in patients that are diagnosed with primary malignancy on their lung. Lung cancer patients with brain metastasis tend to have a poor survivability, which is less than 6 months in median. Therefore, an early and eff...

Automated Grading of Gliomas using Deep Learning in Digital Pathology Images: A modular approach with ensemble of convolutional neural networks.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Brain glioma is the most common primary malignant brain tumors in adults with different pathologic subtypes: Lower Grade Glioma (LGG) Grade II, Lower Grade Glioma (LGG) Grade III, and Glioblastoma Multiforme (GBM) Grade IV. The survival and treatment...

Hybrid RGSA and Support Vector Machine Framework for Three-Dimensional Magnetic Resonance Brain Tumor Classification.

TheScientificWorldJournal
A novel hybrid approach for the identification of brain regions using magnetic resonance images accountable for brain tumor is presented in this paper. Classification of medical images is substantial in both clinical and research areas. Magnetic reso...

An Automatic Learning-Based Framework for Robust Nucleus Segmentation.

IEEE transactions on medical imaging
Computer-aided image analysis of histopathology specimens could potentially provide support for early detection and improved characterization of diseases such as brain tumor, pancreatic neuroendocrine tumor (NET), and breast cancer. Automated nucleus...

Investigating the clinical advantages of a robotic linac equipped with a multileaf collimator in the treatment of brain and prostate cancer patients.

Journal of applied clinical medical physics
The purpose of this study was to evaluate the performance of a commercially avail-able CyberKnife system with a multileaf collimator (CK-MLC) for stereotactic body radiotherapy (SBRT) and standard fractionated intensity-modulated radiotherapy (IMRT) ...

A Type-2 Fuzzy Image Processing Expert System for Diagnosing Brain Tumors.

Journal of medical systems
The focus of this paper is diagnosing and differentiating Astrocytomas in MRI scans by developing an interval Type-2 fuzzy automated tumor detection system. This system consists of three modules: working memory, knowledge base, and inference engine. ...

Supervised machine learning-based classification scheme to segment the brainstem on MRI in multicenter brain tumor treatment context.

International journal of computer assisted radiology and surgery
PURPOSE: To constrain the risk of severe toxicity in radiotherapy and radiosurgery, precise volume delineation of organs at risk is required. This task is still manually performed, which is time-consuming and prone to observer variability. To address...

Blurring the boundaries between frame-based and frameless stereotaxy: feasibility study for brain biopsies performed with the use of a head-mounted robot.

Journal of neurosurgery
OBJECT: Frame-based stereotactic interventions are considered the gold standard for brain biopsies, but they have limitations with regard to flexibility and patient comfort because of the bulky head ring attached to the patient. Frameless image guida...