| DC 欄位 |
值 |
語言 |
| DC.contributor | 電機工程學系 | zh_TW |
| DC.creator | 彭徐鈞 | zh_TW |
| DC.creator | Syu-Jyun Peng | en_US |
| dc.date.accessioned | 2014-7-22T07:39:07Z | |
| dc.date.available | 2014-7-22T07:39:07Z | |
| dc.date.issued | 2014 | |
| dc.identifier.uri | http://ir.lib.ncu.edu.tw:88/thesis/view_etd.asp?URN=985401010 | |
| dc.contributor.department | 電機工程學系 | zh_TW |
| DC.description | 國立中央大學 | zh_TW |
| DC.description | National Central University | en_US |
| dc.description.abstract | 磁振造影包含病理相關資訊，根據磁振造影所得到的生物標記具診斷與治療價值，但是準確檢測此類生物標記具挑戰性，因為疾病的病灶在磁振造影上通常無法直接辨識，甚至有些疾病在磁振造影上並無表現出其病灶。急性缺血性腦中風在磁振造影上有病灶表現，新皮質癲癇神經疾病則無；本論文針對這些有病灶與無病灶的磁振造影生物標記提出自動偵測方法。對於在磁振造影上有病灶表現的急性缺血性腦中風，本論文提出一電腦輔助自動分割和量化方法以辨識腦部梗塞區與白質病變區並且計算這些病灶之體積。此方法使用多重磁振造影，根據病灶的磁振造影強度分布的統計圖定義一個可以自動調整的強度門檻值來區分病灶區與非病灶區。此方法與傳統使用的半自動方法所得到的結果具高度一致性。對於在磁振造影上無表現出病灶的新皮質癲癇神經疾病，本論文提出的方法將磁振造影腦部結構標記模板變形轉化成個人化的神經解剖結構圖，挑選出感興趣的白質纖維與腦深部灰質結構，以探討這些結構與癲癇發作的關聯性。本論文所提出的磁振造影生物標記自動擷取方法利於探索在磁振造影上有表現出病灶以及無表現出病灶的腦神經疾病，以輔助臨床診斷、確定疾病的風險、以及協助引導治療和預後。 | zh_TW |
| dc.description.abstract | Magnetic Resonance Image (MRI) contains pathology-related information. Detection of MRI-based biomarkers is of diagnostic and therapeutic value. Accurate detection of this type of markers is challenging because they may not be directly discernible and some are even non-lesional on conventional MRI. This dissertation presents different methods for finding lesional biomarkers of acute ischemic stroke and non-lesional ones of neocortical seizures. For lesional biomarkers of acute ischemic stroke, we proposed a computer-assisted segmentation and quantification method to depict cerebral infarct and white matter hyperintensities (WMH). The cerebral infarct and WMH volume were measured based on the histographic distribution of lesions to define self-adjusted intensity thresholds using multispectral MRI. The proposed method attained high agreement with the semi-automatic method. For non-lesional biomarkers of neocortical epilepsy, a popular fiber-labeled MRI template was transformed to each subject’s neuroanatomy to generate personalized atlases for objective and automatic region-of-interest (ROI) demarcation. We investigated supratentorial white matter and subcortical gray matter structures from high-resolution raw structural images and diffusion tensor images with automatic ROI registrations in neocortical seizures. The automatic methods presented in this dissertation facilitates the exploration of lesional and non-lesional biomarkers of neurological disorders for assisting the clinical diagnosis, identifying the risk, and helping guide the treatment and prognosis of the diseases. | en_US |
| DC.subject | 磁振造影 | zh_TW |
| DC.subject | 急性缺血性腦中風 | zh_TW |
| DC.subject | 腦部梗塞 | zh_TW |
| DC.subject | 白質病變 | zh_TW |
| DC.subject | 新皮質癲癇 | zh_TW |
| DC.subject | 神經路徑 | zh_TW |
| DC.subject | 腦深部灰質 | zh_TW |
| DC.subject | Magnetic Resonance Imaging | en_US |
| DC.subject | Acute ischemic stroke | en_US |
| DC.subject | Cerebral Infarction | en_US |
| DC.subject | White matter hyperintensity | en_US |
| DC.subject | Focal neocortical epilepsy | en_US |
| DC.subject | Supratentorial neural pathways | en_US |
| DC.subject | Subcortical gray matter | en_US |
| DC.title | 以磁振造影探究有病灶及無病灶神經疾病的自動偵測方法之開發 | zh_TW |
| dc.language.iso | zh-TW | zh-TW |
| DC.title | Development of Automatic Detection Methods for Exploration of Lesional and Non-lesional Neurological Disorders with Magnetic Resonance Imaging | en_US |
| DC.type | 博碩士論文 | zh_TW |
| DC.type | thesis | en_US |
| DC.publisher | National Central University | en_US |