• Journal of Korean Neurosurgical Society
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• v.30 no.1
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• pp.78-80
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• 2001

The bone formation accompanied with other diseases in brain has been rarely reported. Furthermore, it has not been reported without any specific disease. We report a case of a 27 year old female who was referred to our hospital because of the incidentally found calcified lesion in plain X-ray of the skull. The CT and MRI of the brain showed a calcification with minimal enhancement at left parietal area. The calcified lesion was removed and biopsy was performed with stereotactic guided craniotomy. Pathologically, the lesion was confirmed as the membranous bone which was composed of bony trabeculations with osteocytes and the biopsy from adjacent area to the bone revealed a gliosis without any other disease.

• Brain Tumor Research and Treatment
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• v.6 no.2
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• pp.92-96
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• 2018

A 59-year-old patient with a history of hepatocellular carcinoma presented with decreased consciousness and left hemiparesis. A rim-enhanced mass lesion without diffusion restriction was observed in contrast-enhanced MRI including diffusion-weighted imaging. Based on these findings, metastatic brain tumor was suspected. However, brain abscess (BA) was diagnosed after multiple bacterial colonies were observed in aspiration biopsy. Initial conventional antibiotic treatment including vancomycin had failed, so linezolid was used as second-line therapy. As a result, infection signs and clinical symptoms were resolved. We report a case with atypical imaging features and antibiotic susceptibility of a BA in an immunocompromised patient undergoing chemotherapy.

• Parasites, Hosts and Diseases
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• v.60 no.1
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• pp.35-38
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• 2022

Cerebral toxoplasmosis is often life-threatening in an immunocompromised patient due to delayed diagnosis and treatment. Several differential diagnoses could be possible only with preoperative brain images of cerebral toxoplasmosis which show multiple rim-enhancing lesions. Due to the rarity of cerebral toxoplasmosis cases in Korea, the diagnosis and treatment are often delayed. This paper concerns a male patient whose cerebral toxoplasmosis was activated 21 years post kidney transplantation. Brain open biopsy was decided to make an exact diagnosis. Cerebral toxoplasmosis was confirmed by immunohistochemistry and PCR analyses of the tissue samples. Although cerebral toxoplasmosis was under control with medication, the patient did not recover clinically and died due to sepsis and recurrent gastrointestinal bleeding.

• Journal of Korea Multimedia Society
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• v.25 no.8
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• pp.1233-1241
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• 2022

Tumors of the brain are the deadliest, with a life expectancy of only a few years for those with the most advanced forms. Diagnosing a brain tumor is critical to developing a treatment plan to help patients with the disease live longer. A misdiagnosis of brain tumors will lead to incorrect medical treatment, decreasing a patient's chance of survival. Radiologists classify brain tumors via biopsy, which takes a long time. As a result, the doctor will need an automatic classification system to identify brain tumors. Image classification is one application of the deep learning method in computer vision. One of the deep learning's most powerful algorithms is the convolutional neural network (CNN). This paper will introduce a novel deep learning structure and image gradient to classify brain tumors. Meningioma, glioma, and pituitary tumors are the three most popular forms of brain cancer represented in the Figshare dataset, which contains 3,064 T1-weighted brain images from 233 patients. According to the numerical results, our method is more accurate than other approaches.

• Annals of Clinical Neurophysiology
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• v.24 no.2
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• pp.63-67
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• 2022

Primary central nervous system lymphoma (PCNSL) is a type of non-Hodgkin lymphoma confined to the central nervous system. Its diagnosis requires a stereotactic biopsy, which is an invasive procedure. Cerebrospinal fluid (CSF) analysis is less invasive and easier to perform than a stereotactic biopsy. We hereby report a PCNSL case diagnosed using CSF analysis and treated with systemic chemotherapy.

• Journal of Korean Neurosurgical Society
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• v.37 no.4
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• pp.296-299
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• 2005

We report a case of primary central nervous system(CNS) lymphoma in an organ recipient. A 33-years-old man who underwent a renal transplantation 3years previously presented with headache and vomiting. In Brain computed tomography scans and magnetic resonance images showed multiple periventricular cystic rim enhancing masses. Pathologic diagnosis by stereotactic biopsy revealed malignant non-Hodgkins B-cell lymphoma. After pathologic confirmation, methotrexate chemotherapy and whole brain radiation therapy were done. Having experienced such a case, the authors strongly recommend to add primary CNS lymphoma as one of the differential diagnoses to brain abscess, metastatic brain tumor and glioblastoma multiforme in cases of multiple ring enhancing periventricular lesions of immunocompromised patient or organ recipient.

• Nuclear Medicine and Molecular Imaging
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• v.42 no.sup1
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• pp.1-5
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• 2008

Primary brain tumor accounts for 1.4% of entire cancer. For males between the ages of 15 and 34 years, central nervous system tumors account for the leading cause of cancer death. $^{18}F-FDG$ PET has been reported that it can provide important diagnostic information relating to tumor grading and differentiation from non- tumorous condition. In addition, the degree of FDG metabolism carries prognostic significance. By mapping the metabolic pattern of heterogeneous tumors, $^{18}F-FDG$ PET can aid in targeting for stereotactic biopsy by selecting the subregions within the tumor that are most hypermetabolic and potentially have the highest grade. According to clinical research data, FOG PET is expected to be a helpful diagnostic tool in the management of brain tumors.

• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.101-110
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• 2022

Histopathological analysis of biopsy specimens is still used for diagnosis and classifying the brain tumors today. The available procedures are intrusive, time consuming, and inclined to human error. To overcome these disadvantages, need of implementing a fully automated deep learning-based model to classify brain tumor into multiple classes. The proposed CNN model with an accuracy of 92.98 % for categorizing tumors into five classes such as normal tumor, glioma tumor, meningioma tumor, pituitary tumor, and metastatic tumor. Using the grid search optimization approach, all of the critical hyper parameters of suggested CNN framework were instantly assigned. Alex Net, Inception v3, Res Net -50, VGG -16, and Google - Net are all examples of cutting-edge CNN models that are compared to the suggested CNN model. Using huge, publicly available clinical datasets, satisfactory classification results were produced. Physicians and radiologists can use the suggested CNN model to confirm their first screening for brain tumor Multi-classification.

• Journal of Korea Multimedia Society
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• v.23 no.12
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• pp.1486-1495
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• 2020

The analysis of digital microscopy images plays a vital role in computer-aided diagnosis (CAD) and prognosis. The main purpose of this paper is to develop a machine learning technique to predict the histological grades in prostate biopsy. To perform a multiclass classification, an AI-based deep learning algorithm, a multichannel convolutional neural network (MCCNN) was developed by connecting layers with artificial neurons inspired by the human brain system. The histological grades that were used for the analysis are benign, grade 3, grade 4, and grade 5. The proposed approach aims to classify multiple patterns of images extracted from the whole slide image (WSI) of a prostate biopsy based on the Gleason grading system. The Multichannel Convolution Neural Network (MCCNN) model takes three input channels (Red, Green, and Blue) to extract the computational features from each channel and concatenate them for multiclass classification. Stain normalization was carried out for each histological grade to standardize the intensity and contrast level in the image. The proposed model has been trained, validated, and tested with the histopathological images and has achieved an average accuracy of 96.4%, 94.6%, and 95.1%, respectively.

• Investigative Magnetic Resonance Imaging
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• v.21 no.3
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• pp.195-198
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• 2017

Idiopathic brain herniation is a rare condition. We believe that this is the first reported case of idiopathic herniation of the lingual gyrus. The case involves a 57-year-old woman presenting with frontal headache without overt visual symptoms. Magnetic resonance imaging (MRI) revealed an idiopathic herniation of the lingual gyrus of the occipital lobe extending into the quadrigeminal cistern. No other adjacent intracranial abnormalities were observed. Although some conditions may be considered in the differential diagnosis, accurate diagnosis of idiopathic brain herniation in medical practice can prevent unnecessary additional imaging procedures and invasive open biopsy in patients with typical imaging findings.