tumor detection and isolation in magnetic resonance imaging (MRI) is a significant consideration, but when done manually by people, it is very time consuming and may not be accurate. Also, the appearance of the tumor tissue varies from patient to patient, and there are similarities between the tumor and the natural tissue of the brain. In this paper, we have tried to provide an automated method for diagnosing and displaying brain tumors in MRI images. Images of patients with glioblastoma were used after applying pre-processing and removing areas that have no useful information (such as eyes, scalp, etc.). We used a bounding box algorithm, to create a projection for to determining the initial range of the tumor in the next step, an artificial bee colony algorithm, to determine an initial point of the tumor area and then the Grow cut algorithm for, the exact boundary of the tumor area. Our method is automatic and extensively independent of the operator. comparison between results of 12 patients in our method with other similar methods indicate a high accuracy of the proposed method (about 98%) in comparison s.

Background: brain and spinal cord tumors are the most frequent neoplasms after leukemia in children. brain stem glioma is responsible for 10-20% of brain tumors in this group and often found in pons presenting with cerebellar signs, cranial nerve palsies, pyramidal signs and eventually increased intracranial pressure Case Report: In this article we reported an 11 year old girl affected with brain stem tumor with signs of headache, dizziness, vomiting and ataxia. Strabismus due to palsy of sixth cranial nerve, and dysarthria was observed.Conclusion: Children complaining of vomiting, headache and dizziness for a long time must be assessed for brain tumor in posterior fossa that sometimes may lead to increased intracranial pressure. An exact neurological examination can be worth guide to diagnosis.

Background: Very few studies have utilized specific criteria to assess mental disorders in brain tumor patients. This study aimed to diagnose mental disorders in this population using DSM-IV (depression, sleep, and mood) criteria.Methods: From March 2007 to July 2009, the surgically treated patients with intracranial neoplasm were included in the study. These patients were examined in an ambulatory neuro-oncology clinic setting using a structured psychiatric interview which followed current DSM-IV diagnostic criteria.Results: This study is based on the clinical data of 89 patients with brain tumor. The mean age was 42.2 years old. Fifty five percent (55 %) of the patients were male. In our study, the prevalence of mild depression was about 30% for males and 38% for females. Before tumor operation, severe anxious as well as severe obsessive-compulsive symptoms were present in 14% of males. In females, 29% of the subjects had reported to have severe anxiousness and 25% severe obsessive symptoms.Conclusion: Depressive symptoms as well as anxious and obsessive psychopathology were shown to be prevalent signs among patients with brain tumor. The associated factors are tumor location, patient’s premorbid psychiatric status, cognitive symptoms and adaptive or maladaptive response to stress.