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BACKGROUND: Advances in white matter tractography enhance neurosurgical planning and glioma resection, but white matter tractography is limited by biological variables such as edema, mass effect, and tract infiltration or selection biases related to regions of interest or fractional anisotropy values. OBJECTIVE: To provide an automated tract identification paradigm that corrects for artifacts created by tumor edema and infiltration and provides a consistent, accurate method of fiber bundle identification. METHODS: An automated tract identification paradigm was developed and evaluated for glioma surgery. A fiber bundle atlas was generated from 6 healthy participants. Fibers of a test set (including 3 healthy participants and 10 patients with brain tumors) were clustered adaptively with this atlas. Reliability of the identified tracts in both groups was assessed by comparison with 2 experts with the Cohen κ used to quantify concurrence. We evaluated 6 major fiber bundles: cingulum bundle, fornix, uncinate fasciculus, arcuate fasciculus, inferior fronto-occipital fasciculus, and inferior longitudinal fasciculus, the last 3 tracts mediating language function. RESULTS: The automated paradigm demonstrated a reliable and practical method to identify white mater tracts, despite mass effect, edema, and tract infiltration. When the tumor demonstrated significant mass effect or shift, the automated approach was useful for providing an initialization to guide the expert with identification of the specific tract of interest. CONCLUSION: We report a reliable paradigm for the automated identification of white matter pathways in patients with gliomas. This approach should enhance the neurosurgical objective of maximal safe resections. ABBREVIATIONS: AF, arcuate fasciculusDTI, diffusion tensor imagingIFOF, inferior fronto-occipital fasciculusILF, inferior longitudinal fasciculusROI, region of interestWM, white matter.

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Otologic surgery is performed for a variety of reasons including treatment of recurrent ear infections, alleviation of dizziness, and restoration of hearing loss. A typical ear surgery consists of a tympanomastoidectomy in which both the middle ear is explored via a tympanic membrane flap and the bone behind the ear is removed via mastoidectomy to treat disease and/or provide additional access. The mastoid dissection is performed using a high-speed drill to excavate bone based on a pre-operative CT scan. Intraoperatively, the surface of the mastoid component of the temporal bone provides visual feedback allowing the surgeon to guide their dissection. Dissection begins in "safe areas" which, based on surface topography, are believed to be correlated with greatest distance from surface to vital anatomy thus decreasing the chance of injury to the brain, large blood vessels (e.g. the internal jugular vein and internal carotid artery), the inner ear, and the facial nerve. "Safe areas" have been identified based on surgical experience with no identifiable studies showing correlation of the surface with subsurface anatomy. The purpose of our study was to investigate whether such a correlation exists. Through a three-step registration process, we defined a correspondence between each of twenty five clinically-applicable temporal bone CT scans of patients and an atlas and explored displacement and angular differences of surface topography and depth of critical structures from the surface of the skull. The results of this study reflect current knowledge of osteogenesis and anatomy. Based on two features (distance and angular difference), two regions (suprahelical and posterior) of the temporal bone show the least variability between surface and subsurface anatomy.

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Accurate anatomic co-registration is a prerequisite for identifying structural and functional changes in longitudinal studies of brain plasticity. Current MRI methods permit collection of brain images across multiple scales, ranging from whole brain at relatively low resolution (≥1 mm), to local brain areas at the level of cortical layers and columns (∼100 µm) in the same session, allowing detection of subtle structural changes on a similar spatial scale. To measure these changes reliably, high resolution structural and functional images of local brain regions must be registered accurately across imaging sessions. The present study describes a robust fully automated strategy for the registration of high resolution structural images of brain sub-volumes to lower resolution whole brain images collected within a session, and the registration of partially overlapping high resolution MRI sub-volumes ("slabs") across imaging sessions. In high field (9.4 T) reduced field-of-view high resolution structural imaging studies using a surface coil in an anesthetized non-human primate model, this fully automated coregistration pipeline was robust in the face of significant inhomogeneities in image intensity and tissue contrast arising from the spatially inhomogeneous transmit and receive properties of the surface coil, achieving a registration accuracy of 30±15 µm between sessions.

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Dynamic structural and functional remodeling of the Central Nervous System occurs throughout the lifespan of the organism from the molecular to the systems level. MRI offers several advantages to observe this phenomenon: it is non-invasive and non-destructive, the contrast can be tuned to interrogate different tissue properties and imaging resolution can range from cortical columns to whole brain networks in the same session. To measure these changes reliably, functional maps generated over time with high resolution fMRI need to be registered accurately. This article presents a new method for the automatic registration of thin cortical MR volumes that are aligned with the functional maps. These acquisitions focus on the primary somato-sensory cortex, a region in the anterior parietal part of the brain, responsible for fine touch and proprioception. Currently, these slabs are acquired in approximately the same orientation from acquisition to acquisition and then registered by hand. Because they only cover a small portion of the cortex, their direct automatic registration is difficult. To address this issue, we propose a method relying on an intermediate image, acquired with a surface coil that covers a larger portion of the head to which the slabs can be registered. Because images acquired with surface coils suffer from severe intensity attenuation artifact, we also propose a method to register these. The results from data sets obtained with 3 squirrel monkeys show a registration accuracy of 30 micrometers.).

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Graph Cuts have been shown as a powerful interactive segmentation technique in several medical domains. We propose to automate the Graph Cuts in order to automatically segment Multiple Sclerosis (MS) lesions in MRI. We replace the manual interaction with a robust EM-based approach in order to discriminate between MS lesions and the Normal Appearing Brain Tissues (NABT). Evaluation is performed in synthetic and real images showing good agreement between the automatic segmentation and the target segmentation. We compare our algorithm with the state of the art techniques and with several manual segmentations. An advantage of our algorithm over previously published ones is the possibility to semi-automatically improve the segmentation due to the Graph Cuts interactive feature.

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