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Brain segmentation

L Vidyaratne, M Alam, Z Shboul, K M Iftekharuddin
Brain tumor segmentation is a fundamental step in surgical treatment and therapy. Many hand-crafted and learning based methods have been proposed for automatic brain tumor segmentation from MRI. Studies have shown that these approaches have their inherent advantages and limitations. This work proposes a semantic label fusion algorithm by combining two representative state-of-the-art segmentation algorithms: texture based hand-crafted, and deep learning based methods to obtain robust tumor segmentation. We evaluate the proposed method using publicly available BRATS 2017 brain tumor segmentation challenge dataset...
2018: Proceedings of SPIE
Jae W Song, Gerlinde M Gruber, Janina M Patsch, Rainer Seidl, Daniela Prayer, Gregor Kasprian
Prenatal detection of abnormal white matter tracts might serve as a structural marker for altered neurodevelopment. As a result of many technical and patient-related challenges, the accuracy of prenatal tractography remains unknown. We hypothesized that characteristics of prenatal tractography of the corpus callosum and corticospinal tracts derived from fetal diffusion tensor imaging (DTI) data are accurate and predictive of the integrity of these tracts postnatally. We compared callosal and corticospinal tracts of 12 subjects with paired prenatal (age: 23-35 gestational weeks) and postnatal (age: 1 day to 2 years) DTI examinations (b values of 0 s/mm2 and 700 s/mm2 , 16 gradient encoding directions) using deterministic tractography...
April 2018: Pediatric Radiology
Fabian Wenzel, Carsten Meyer, Thomas Stehle, Jochen Peters, Susanne Siemonsen, Christian Thaler, Lyubomir Zagorchev
This work presents a novel approach for the rapid segmentation of clinically relevant subcortical brain structures in T1-weighted MRI by utilizing a shape-constrained deformable surface model. In contrast to other approaches for segmenting brain structures, its design allows for parallel segmentation of individual brain structures within a flexible and robust hierarchical framework such that accurate adaptation and volume computation can be achieved within a minute of processing time. Furthermore, adaptation is driven by local and not global contrast, potentially relaxing requirements with respect to preprocessing steps such as bias-field correction...
March 9, 2018: Medical Image Analysis
Haotian Lin, Li Zhang, Duoru Lin, Wan Chen, Yi Zhu, Chuan Chen, Kevin C Chan, Yizhi Liu, Weirong Chen
BACKGROUND: Visual function and brain function decline concurrently with aging. Notably, cataract patients often present with accelerated age-related decreases in brain function, but the underlying mechanisms are still unclear. Optical structures of the anterior segment of the eyes, such as the lens and cornea, can be readily reconstructed to improve refraction and vision quality. However, the effects of visual restoration on human brain function and structure remain largely unexplored...
March 7, 2018: EBioMedicine
Jyoti Singh Kirar, R K Agrawal
This paper presents a novel algorithm (CVSTSCSP) for determining discriminative features from an optimal combination of temporal, spectral and spatial information for motor imagery brain computer interfaces. The proposed method involves four phases. In the first phase, EEG signal is segmented into overlapping time segments and bandpass filtered through frequency filter bank of variable size subbands. In the next phase, features are extracted from the segmented and filtered data using stationary common spatial pattern technique (SCSP) that can handle the non- stationarity and artifacts of EEG signal...
March 16, 2018: Journal of Medical Systems
Sunao Mizumura, Kazuhiro Nishikawa, Akihiro Murata, Kosei Yoshimura, Nobutomo Ishii, Tadashi Kokubo, Miyako Morooka, Akiko Kajiyama, Atsuro Terahara
OBJECTIVE: In Japan, the Southampton method for dopamine transporter (DAT) SPECT is widely used to quantitatively evaluate striatal radioactivity. The specific binding ratio (SBR) is the ratio of specific to non-specific binding observed after placing pentagonal striatal voxels of interest (VOIs) as references. Although the method can reduce the partial volume effect, the SBR may fluctuate due to the presence of low-count areas of cerebrospinal fluid (CSF), caused by brain atrophy, in the striatal VOIs...
March 15, 2018: Annals of Nuclear Medicine
Z Y Jia, L B Zhao, D H Lee
BACKGROUND AND PURPOSE: Segmental intracranial dolichoectasia of the distal ICA is a feature of PHACE syndrome or a sporadic phenomenon. We evaluated the relationship between intracranial dolichoectasia of the distal ICA and PHACE syndrome and illustrated the characteristic radiologic findings of the lesions. MATERIALS AND METHODS: Intracranial dolichoectasia of the distal ICA was identified in 20 patients at our institution from 2005 to 2016 through a review of diagnostic cerebral angiography results...
March 15, 2018: AJNR. American Journal of Neuroradiology
Heather T Whittaker, Shenghua Zhu, Domenico L Di Curzio, Richard Buist, Xin-Min Li, Suzanna Noy, Frances K Wiseman, Jonathan D Thiessen, Melanie Martin
Alzheimer's disease (AD) pathology causes microstructural changes in the brain. These changes, if quantified with magnetic resonance imaging (MRI), could be studied for use as an early biomarker for AD. The aim of our study was to determine if T1 relaxation, diffusion tensor imaging (DTI), and quantitative magnetization transfer imaging (qMTI) metrics could reveal changes within the hippocampus and surrounding white matter structures in ex vivo transgenic mouse brains overexpressing human amyloid precursor protein with the Swedish mutation...
March 12, 2018: Magnetic Resonance Imaging
Eli Gibson, Wenqi Li, Carole Sudre, Lucas Fidon, Dzhoshkun I Shakir, Guotai Wang, Zach Eaton-Rosen, Robert Gray, Tom Doel, Yipeng Hu, Tom Whyntie, Parashkev Nachev, Marc Modat, Dean C Barratt, Sébastien Ourselin, M Jorge Cardoso, Tom Vercauteren
BACKGROUND AND OBJECTIVES: Medical image analysis and computer-assisted intervention problems are increasingly being addressed with deep-learning-based solutions. Established deep-learning platforms are flexible but do not provide specific functionality for medical image analysis and adapting them for this domain of application requires substantial implementation effort. Consequently, there has been substantial duplication of effort and incompatible infrastructure developed across many research groups...
May 2018: Computer Methods and Programs in Biomedicine
Fernando Yepes-Calderon, Marvin D Nelson, J Gordon McComb
The picture archiving and communications system (PACS) is currently the standard platform to manage medical images but lacks analytical capabilities. Staying within PACS, the authors have developed an automatic method to retrieve the medical data and access it at a voxel level, decrypted and uncompressed that allows analytical capabilities while not perturbing the system's daily operation. Additionally, the strategy is secure and vendor independent. Cerebral ventricular volume is important for the diagnosis and treatment of many neurological disorders...
2018: PloS One
Rainer Benndorf, Robert R Gilmont, Sahoko Hirano, Richard F Ransom, Peter R Jungblut, Martin Bommer, James E Goldman, Michael J Welsh
When analyzing small stress proteins of rat and human tissues by electrophoretic methods followed by western blotting, and using the anti-HspB1/anti-HspB5 antibody clone 8A7, we unexpectedly found a protein with a molecular mass of ~44 kDa. On two-dimensional gels, this protein resolved into four distinct species. Electrophoretic and immunological evidence suggests that this 44 kDa protein is a derivative of HspB5, most likely a covalently linked HspB5 dimer. This HspB5-like 44 kDa protein (HspB5L-P44) is particularly abundant in rat heart, brain, and renal cortex and glomeruli...
March 14, 2018: Cell Stress & Chaperones
Ruobing Huang, Ana Namburete, Alison Noble
We present a general framework for automatic segmentation of fetal brain structures in ultrasound images inspired by recent advances in machine learning. The approach is based on a region descriptor that characterizes the shape and local intensity context of different neurological structures without explicit models. To validate our framework, we present experiments to segment two fetal brain structures of clinical importance that have quite different ultrasonic appearances-the corpus callosum (CC) and the choroid plexus (CP)...
January 2018: Journal of Medical Imaging
Laura Gaetano, Dieter A Häring, Ernst-Wilhelm Radue, Nicole Mueller-Lenke, Avinash Thakur, Davorka Tomic, Ludwig Kappos, Till Sprenger
OBJECTIVE: To study the effect of fingolimod on deep gray matter (dGM), thalamus, cortical GM (cGM), white matter (WM), and ventricular volume (VV) in patients with relapsing-remitting multiple sclerosis (RRMS). METHODS: Data were pooled from 2 phase III studies. A total of 2,064 of 2,355 (88%) contributed to the analysis: fingolimod 0.5 mg n = 783, fingolimod 1.25 mg n = 799, or placebo n = 773. Percentage change from baseline in dGM and thalamic volumes was evaluated with FMRIB's Integrated Registration & Segmentation Tool; WM, cGM, and VV were evaluated with structural image evaluation using normalization of atrophy cross-sectional version (SIENAX) at months 12 and 24...
March 14, 2018: Neurology
Jacque P K Ip, Ikue Nagakura, Jeremy Petravicz, Keji Li, Erik A C Wiemer, Mriganka Sur
Microdeletion of a region in chromosome 16p11.2 increases susceptibility to autism. Although this region contains exons of 29 genes, disrupting only a small segment of the region, which spans 5 genes, is sufficient to cause autistic traits. One candidate gene in this critical segment is MVP , which encodes for the major vault protein (MVP) that has been implicated in regulation of cellular transport mechanisms. MVP expression levels in MVP +/- mice closely phenocopy those of 16p11.2 mutant mice, suggesting that MVP +/- mice may serve as a model of MVP function in 16p11...
March 14, 2018: Journal of Neuroscience: the Official Journal of the Society for Neuroscience
Alicja Kalinowska-Łyszczarz, Mikołaj A Pawlak, Aleksandra Wyciszkiewicz, Katarzyna Pawlak-Buś, Piotr Leszczyński, Mariusz Puszczewicz, Włodzimierz Paprzycki, Wojciech Kozubski, Sławomir Michalak
OBJECTIVE: Central nervous system (CNS) involvement in systemic lupus erythematosus (SLE) remains poorly understood. Damage within the CNS is driven by the autoimmune response; however, immunopathophysiology of neuropsychiatric (NP) SLE is multifactorial. Immune cell neurotrophin production could be neuroprotective against autoimmunity-driven CNS damage, as has been shown in multiple sclerosis. The aim of this study was to establish whether immune cell neurotrophin production is associated with damage severity in NPSLE...
March 14, 2018: Neuroimmunomodulation
George Inana, Christopher Murat, Weijun An, Xiang Yao, Ian R Harris, Jing Cao
BACKGROUND: Age-related macular degeneration (AMD) is a leading cause of blindness among the elderly characterized by retinal pigment epithelium (RPE) degeneration with accumulation of abnormal intracellular deposits (lipofuscin) and photoreceptor death. RPE is vital for the retina and integrity of photoreceptors through its phagocytic function which is closely linked to formation of lipofuscin through daily phagocytosis of discarded photoreceptor outer segments (POS). Although phagocytosis has been implicated in AMD, it has not been directly shown to be altered in AMD...
March 13, 2018: Journal of Translational Medicine
Raghavendra Rao, Motaz Nashawaty, Saher Fatima, Kathleen Ennis, Ivan Tkac
Hyperglycemia (blood glucose concentration >150 mg/dL) is common in extremely low gestational age newborns (ELGANs; birth at <28 week gestation). Hyperglycemia increases the risk of brain injury in the neonatal period. The long-term effects are not well understood. In adult rats, hyperglycemia alters hippocampal energy metabolism. The effects of hyperglycemia on the developing hippocampus were studied in rat pups. In Experiment 1, recurrent hyperglycemia of graded severity (moderate hyperglycemia (moderate-HG), mean blood glucose 214...
March 13, 2018: NMR in Biomedicine
Evangelia Tsolaki, Angela Downes, William Speier, W Jeff Elias, Nader Pouratian
Magnetic Resonance-guided Focused UltraSound (MRgFUS) offers an incisionless approach to treat essential tremor (ET). Due to lack of evident internal anatomy on traditional structural imaging, indirect targeting must still be used to localize the lesion. Here, we investigate the potential predictive value of probabilistic tractography guided thalamic targeting by defining how tractography-defined targets, lesion size and location, and clinical outcomes interrelate. MR imaging and clinical outcomes from 12 ET patients that underwent MRgFUS thalamotomy in a pilot study at the University of Virginia were evaluated in this analysis...
2018: NeuroImage: Clinical
R Guerrero, C Qin, O Oktay, C Bowles, L Chen, R Joules, R Wolz, M C Valdés-Hernández, D A Dickie, J Wardlaw, D Rueckert
White matter hyperintensities (WMH) are a feature of sporadic small vessel disease also frequently observed in magnetic resonance images (MRI) of healthy elderly subjects. The accurate assessment of WMH burden is of crucial importance for epidemiological studies to determine association between WMHs, cognitive and clinical data; their causes, and the effects of new treatments in randomized trials. The manual delineation of WMHs is a very tedious, costly and time consuming process, that needs to be carried out by an expert annotator (e...
2018: NeuroImage: Clinical
Muhammad Febrian Rachmadi, Maria Del C Valdés-Hernández, Maria Leonora Fatimah Agan, Carol Di Perri, Taku Komura
We propose an adaptation of a convolutional neural network (CNN) scheme proposed for segmenting brain lesions with considerable mass-effect, to segment white matter hyperintensities (WMH) characteristic of brains with none or mild vascular pathology in routine clinical brain magnetic resonance images (MRI). This is a rather difficult segmentation problem because of the small area (i.e., volume) of the WMH and their similarity to non-pathological brain tissue. We investigate the effectiveness of the 2D CNN scheme by comparing its performance against those obtained from another deep learning approach: Deep Boltzmann Machine (DBM), two conventional machine learning approaches: Support Vector Machine (SVM) and Random Forest (RF), and a public toolbox: Lesion Segmentation Tool (LST), all reported to be useful for segmenting WMH in MRI...
February 17, 2018: Computerized Medical Imaging and Graphics: the Official Journal of the Computerized Medical Imaging Society
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