Meningiomas are the most common primary intracranial tumour. Although external beam
radiotherapy and radiosurgery are well-established treatments, affording local control rates …

BACKGROUND Classifying brain tumors accurately is crucial for treatment and prognosis.
Machine learning (ML) shows great promise in improving tumor classification accuracy. This …

Background The reliability and validity of magnetic resonance imaging (MRI) for detecting
neoplastic, inflammatory, and cerebrovascular brain lesions in dogs are unknown …

Justification Automatic brain tumor classification by MRS has been under development for
more than a decade. Nonetheless, to our knowledge, there are no published evaluations of …

Astrocytomas and oligodendrogliomas represent one third of histologically confirmed canine
brain tumors. Our purpose was to describe the magnetic resonance (MR) imaging features …

We present an agent-based distributed decision support system for the diagnosis and
prognosis of brain tumors developed by the HealthAgents project. HealthAgents is a …

Objectives: Discuss intramedullary, intradural/extramedullary, and extradural spinal tumors
including imaging characteristics with emphasis on MR and advances in treatment …

Magnetic resonance (MR) imaging characteristics are commonly used to help predict
intracranial disease categories in dogs, however, few large studies have objectively …

Simple Summary Within the rapidly evolving landscape of Machine Learning in the medical
field, this paper focuses on the forefront advancements in neuro-oncological radiology. More …

Background Conventional magnetic resonance imaging (MRI) is considered a valuable tool
for preoperative diagnosis of intracranial tumors. We assessed its accuracy in the diagnosis …