• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.39C no.6
• /
• pp.490-496
• /
• 2014

The thickness of knee joint cartilage causes most diseases of knee. Therefore, an articular cartilage segmentation of knee magnetic resonance imaging (MRI) is required to diagnose a knee diagnosis correctly. In particular, fully automatic segmentation method of knee joint cartilage enables an effective diagnosis of knee disease. In this paper, we analyze a well-known level-set based segmentation method in brain MRI, and apply that method to knee MRI with solving some problems from different image characteristics. The proposed method, a fully automatic segmentation in whole process, enables to process faster than previous semi-automatic segmentation methods. Also it can make a three-dimension visualization which provides a specialist with an assistance for the diagnosis of knee disease. In addition, the proposed method provides more accurate results than the existing methods of articular cartilage segmentation in knee MRI through experiments.

• International Journal of Computer Science & Network Security
• /
• v.23 no.11
• /
• pp.183-189
• /
• 2023

A stroke is a medical disease where a blood vessel in the brain ruptures, causes damage to the brain. If the flow of blood and different nutrients to the brain is intermittent, symptoms may occur. Stroke is other reason for loss of life and widespread disorder. The prevalence of stroke is high in growing countries, with ischemic stroke being the high usual category. Many of the forewarning signs of stroke can be recognized the seriousness of a stroke can be reduced. Most of the earlier stroke detections and prediction models uses image examination tools like CT (Computed Tomography) scan or MRI (Magnetic Resonance Imaging) which are costly and difficult to use for actual-time recognition. Machine learning (ML) is a part of artificial intelligence (AI) that makes software applications to gain the exact accuracy to predict the end results not having to be directly involved to get the work done. In recent times ML algorithms have gained lot of attention due to their accurate results in medical fields. Hence in this work, Stroke disease identification system by using Machine Learning algorithm is presented. The ML algorithm used in this work is Artificial Neural Network (ANN). The result analysis of presented ML algorithm is compared with different ML algorithms. The performance of the presented approach is compared to find the better algorithm for stroke identification.

• Investigative Magnetic Resonance Imaging
• /
• v.3 no.1
• /
• pp.47-52
• /
• 1999

Purpose : The purpose of this study was aimed to evaluate the BOLD(blood oxygen level dependent) contrast fMRI(functional MR imaging) in the occipital lobe and to compare with the metabolic changes based on H MRS (MR spectroscopy) and MRSI (MR spectroscopic imaging) before and after visual stimulation Materials and Methods : Healthy human volunteers (eight males and two females with 24-30 year age) participated in this study. All of the BOLD fMRI were acquired on a 1.5T MR with EPI during supervised visual stimulation in the occipital lobe. The red flicker with 8Hz was used for visual stimulation. After imaging acquisition, the MR images were transferred into unix workstation and processed with acquired from the same location based on the activation map. MRSI (magnetic resonance spectroscopic imaging) was also acquired to analyze the lactate changes before and after stimulation. Results : The activation maps were successfully produced by BOLD effect due to visual stimulation. NAA (N-acetyle aspartate)/Cr (creatine) ratio varied only from $1.79{\pm}0.28{\;}to{\;}1.88{\pm}0.20$ in activation area before and after stimulation. However, the signal intensity of lactate was elevated $9.48{\pm}4.38$ times higher than before activation. Lactate metabolite images were consistent with the activation maps. Conclusion : The BOLD contrast fMRI is enough sensitive to detect the activated area in human brain during the visual stimulation. Lactate metabolite map presents the evidence of lactate elevation on the same area of activation.

• Journal of Korean Neurosurgical Society
• /
• v.60 no.6
• /
• pp.667-675
• /
• 2017

Objective : Total resection without consecutive postoperative whole brain radiation therapy is indicated for patients with a single or two sites of brain metastasis, with close follow-up by serial magnetic resonance imaging (MRI). In this study, we explored the effectiveness, usefulness, and safety of this follow-up regimen. Methods : From January 2006 to December 2015, a total of 109 patients (76 males, 33 females) underwent tumor resection as the first treatment for brain metastases (97 patients with single metastases, 12 with two metastases). The mean age was 59.8 years (range 27-80). The location of the 121 tumors in the 109 patients was supratentorial (n=98) and in the cerebellum (n=23). The origin of the primary cancers was lung (n=45), breast (n=17), gastrointestinal tract (n=18), hepatobiliary system (n=8), kidney (n=7), others (n=11), and unknown origin (n=3). The 121 tumors were totally resected. Follow-up involved regular clinical and MRI assessments. Recurrence-free survival (RFS) and overall survival (OS) after tumor resection were analyzed by Kaplan-Meier methods based on clinical prognostic factors. Results : During the follow-up, MRI scans were done for 85 patients (78%) with 97 tumors. Fifty-six of the 97 tumors showed no recurrence without adjuvant local treatment, representing a numerical tumor recurrence-free rate of 57.7%. Mean and median RFS was 13.6 and 5.3 months, respectively. Kaplan-Meier analysis revealed the cerebellar location of the tumor as the only statistically significant prognostic factor related to RFS (p=0.020). Mean and median OS was 15.2 and 8.1 months, respectively. There were no significant prognostic factors related to OS. The survival rate at one year was 8.2% (9 of 109). Conclusion : With close and regular clinical and image follow-up, initial postoperative observation without prompt postoperative radiation therapy can be applied in patients of brain metastasi(e)s when both the tumor(s) are completely resected.

• Journal of Korean Neurosurgical Society
• /
• v.41 no.3
• /
• pp.177-179
• /
• 2007

Most of intradural epidermoid cyst arise as slowly growing extraaxial lesions but purely intracerebral epidermoid cysts are rare. A 39-year-old female presented with a headache during several months. Brain computed tomography [CT] scan showed a mass lesion in the both frontal lobe with heterogenous density approximately $5{\times}5cm$ in size. Magnetic resonance imaging [MRI] revealed a mass of heterogenous signal intensity on T1, T2-weighted image and faint enhancement with gadolinium [Gd]. Through the both interhemispheric approach, mass was removed subtotally except the calcified portion tightly attached to the corpus callosum. The patient discharged without neurological deficit. The authors report a case of epidermoid cyst in the corpus callosum and discuss the pathogenesis of the intraparenchymal epidermoid cyst.

• Clinical Psychopharmacology and Neuroscience
• /
• v.16 no.4
• /
• pp.449-460
• /
• 2018

Objective: Prior functional magnetic resonance imaging (fMRI) work has revealed that children/adolescents with disruptive behavior disorders (DBDs) show dysfunctional reward/non-reward processing of non-social reinforcements in the context of instrumental learning tasks. Neural responsiveness to social reinforcements during instrumental learning, despite the importance of this for socialization, has not yet been previously investigated. Methods: Twenty-nine healthy children/adolescents and 19 children/adolescents with DBDs performed the fMRI social/non-social reinforcement learning task. Participants responded to random fractal image stimuli and received social and non-social rewards/non-rewards according to their accuracy. Results: Children/adolescents with DBDs showed significantly reduced responses within the caudate and posterior cingulate cortex (PCC) to non-social (financial) rewards and social non-rewards (the distress of others). Connectivity analyses revealed that children/adolescents with DBDs have decreased positive functional connectivity between the ventral striatum (VST) and the ventromedial prefrontal cortex (vmPFC) seeds and the lateral frontal cortex in response to reward relative to non-reward, irrespective of its sociality. In addition, they showed decreased positive connectivity between the vmPFC seed and the amygdala in response to non-reward relative to reward. Conclusion: These data indicate compromised reinforcement processing of both non-social rewards and social non-rewards in children/adolescents with DBDs within core regions for instrumental learning and reinforcement-based decision-making (caudate and PCC). In addition, children/adolescents with DBDs show dysfunctional interactions between the VST, vmPFC, and lateral frontal cortex in response to rewarded instrumental actions potentially reflecting disruptions in attention to rewarded stimuli.

• Journal of radiological science and technology
• /
• v.33 no.1
• /
• pp.45-50
• /
• 2010

In this study, we compared the clinical usefulness of SPAIR (Spectral Adiabatic Inversion Recovery) and STIR (Short TI Inversion Recovery) to evaluate the fat tissues precisely. The images of brain axial (n = 20), lumber spine sagittal (n = 20), hip joint coronal (n = 17) and knee joint (n = 25) were obtained by turbo spin echo T2 weighted method on 3T magnetic resonance image. The signal intensity (SI) values were measured using region of interest in fat, muscle tissue, and background noise. The inhomogeneity values were measured using the standard deviation (SD) value divided by the mean values. SD signifies the amount of error which is similar to the imaging heterogeneity. In brain axial images, the SPAIR showed more superior SI and inhomogeneity results than the STIR. In spine, hip and knee images, STIR showed more excellent SI results, but poor inhomogeneity than the SPAIR.

• Journal of Magnetics
• /
• v.17 no.2
• /
• pp.158-162
• /
• 2012

Although 3.0T magnetic resonance imaging (MRI) has the advantages of a higher signal to noise ratio (SNR) and contrast than 1.5T MRI, there are limitations on the contrast between white and grey matter because of the long T1 recovery time when T1 images are obtained using the Spin Echo Technique. To overcome this, T1 weighted images are obtained occasionally using the inversion recovery (IR) technique, which employs a relatively long TR. The aim of this study was to determine the optimal TI in a brain examination when a T1 weighted image is obtained using the IR technique. Eight participants (male: 7, female: 1, average age: $34{\pm}14.11$) with a normal diagnosis were targeted from February 18, 2012 to February 27, 2012, and the contrast between white and grey matter as well as the contrast to noise ratio (CNRs) in each participant were measured. The CNRs of white matter and grey matter were highest at TI = 600, 650, 750, 900, 1050 and 1100 ms when the TR was 1100, 1400, 1700, 2000, 2300 and 2600 ms, respectively. Therefore, as the TIs were $44.425{\pm}0.877%$ of the TRs in the TR range of 1400-2300 ms, the optimal T1 weighted images that describe the contrast between white and grey matter can be obtained if the TIs are compensated for with $44.425{\pm}0.877%$ of the TRs in the time of setting TIs.

• Journal of Veterinary Clinics
• /
• v.29 no.4
• /
• pp.328-330
• /
• 2012

A 13-year-old, neutered male, chihuahua was referred to the Veterinary Medical Teaching Hospital of Chungnam National University with a history of a bilateral mandibular mass, intermittent vomiting, cough, and left sided staggering starting ten days prior. Clinical examination along with radiography, neurologic examination and magnetic resonance imaging (MRI) demonstrated a well-circumscribed and solitary mass in the brain stem. The dura mater was thickened with marked linear enhancement after contrast administration. Based on diagnostic image analysis and histopathologic examination, this case was diagnosed as intracranial meningioma. The patient's symptoms were controlled for 18 months by a combination therapy of prednisolone and lomustine (CCNU), and then he died of at home.

• Progress in Medical Physics
• /
• v.9 no.1
• /
• pp.47-53
• /
• 1998

Nuclear Medicine Images have comparatively poor spatial resolution, making it difficult to relate the functional information which they contain to precise anatomical structures. Anatomical structures useful in the interpretation of SPECT /PET Images were radiolabelled. PET/SPECT Images Provide functional information, whereas MRI mainly demonstrate morphology and anatomical. Fusion or Image Registration improves the information obtained by correlating images from various modalities. Brain Scan were studied on one or more occations using MRI and SPECT. The data were aligned using a point pair methods and surface matching. SPECT and MR Images was tested using a three dimensional water fillable Hoffman Brain Phantom with small marker and PET and MR Image was tested using a patient data. Registration of SPECT and MR Images is feasible and allows more accurate anatomic assessment of sites of abnormal uptake in radiolabeled studies. Point based registration was accurate and easily implemented three dimensional registration of multimodality data set for fusion of clinical anatomic and functional imaging modalities. Accuracy of a surface matching algorithm and homologous feature pair matching for three dimensional image registration of Single Photon Emission Computed Tomography Emission Computed Tomography (SPECT), Positron Emission Tomography (PET) and Magnetic Resonance Images(MRD was tested using a three dimensional water fill able brain phantom and Patients data. Transformation parameter for translation and scaling were determined by homologous feature point pair to match each SPECT and PET scan with MR images.