ABSTRACT Linear and nonlinear adaptive filtering algorithms are described, along with application... more ABSTRACT Linear and nonlinear adaptive filtering algorithms are described, along with applications to signal processing and control problems such as prediction, modeling, inverse modeling, equalization, echo cancelling, noise cancelling, and inverse control.
Evaluating various algorithms for the inter-subject registration of brain magnetic resonance imag... more Evaluating various algorithms for the inter-subject registration of brain magnetic resonance images (MRI) is a necessary topic receiving growing attention. Existing studies evaluated image registration algorithms in specific tasks or using specific databases (e.g., only for skull-stripped images, only for single-site images, etc.). Consequently, the choice of registration algorithms seems task- and usage/parameter-dependent. Nevertheless, recent large-scale, often multi-institutional imaging-related studies create the need and raise the question whether some registration algorithms can 1) generally apply to various tasks/databases posing various challenges; 2) perform consistently well, and while doing so, 3) require minimal or ideally no parameter tuning. In seeking answers to this question, we evaluated 12 general-purpose registration algorithms, for their generality, accuracy and robustness. We fixed their parameters at values suggested by algorithm developers as reported in the literature. We tested them in 7 databases/tasks, which present one or more of 4 commonly-encountered challenges: 1) inter-subject anatomical variability in skull-stripped images; 2) intensity homogeneity, noise and large structural differences in raw images; 3) imaging protocol and field-of-view (FOV) differences in multi-site data; and 4) missing correspondences in pathology-bearing images. Totally 7,562 registrations were performed. Registration accuracies were measured by (multi-)expert-annotated landmarks or regions of interest (ROIs). To ensure reproducibility, we used public software tools, public databases (whenever possible), and we fully disclose the parameter settings. We show evaluation results, and discuss the performances in light of algorithms' similarity metrics, transformation models and optimization strategies. We also discuss future directions for the algorithm development and evaluations.
To augment the analysis of dynamic susceptibility contrast material-enhanced magnetic resonance (... more To augment the analysis of dynamic susceptibility contrast material-enhanced magnetic resonance (MR) images to uncover unique tissue characteristics that could potentially facilitate treatment planning through a better understanding of the peritumoral region in patients with glioblastoma. Institutional review board approval was obtained for this study, with waiver of informed consent for retrospective review of medical records. Dynamic susceptibility contrast-enhanced MR imaging data were obtained for 79 patients, and principal component analysis was applied to the perfusion signal intensity. The first six principal components were sufficient to characterize more than 99% of variance in the temporal dynamics of blood perfusion in all regions of interest. The principal components were subsequently used in conjunction with a support vector machine classifier to create a map of heterogeneity within the peritumoral region, and the variance of this map served as the heterogeneity score. ...
... Proc AMIA Annu Fall Symp. 1997: 896. PMCID: PMC2233418. Copyright notice. A Textual Informati... more ... Proc AMIA Annu Fall Symp. 1997: 896. PMCID: PMC2233418. Copyright notice. A Textual Information Detection and Elimination System for Secure Medical Image Distribution *. James Ze Wang, Michel Bilello, and Gio Wiederhold. ...
The TIHI project addresses the issues that arise when some information must be shared among colla... more The TIHI project addresses the issues that arise when some information must be shared among collaborating, but distinct enterprises. Such enterprises cannot fully share their data and information resources, although some information exchange is essential. ...
Page 1. Protecting Collaboration Gio Wiederholdi Stanford University, CA Michel Bilello Stanford ... more Page 1. Protecting Collaboration Gio Wiederholdi Stanford University, CA Michel Bilello Stanford University, CA ... 1 Page 2. the acceptance of this approach 3 . Uncontrolled sharing of proprietary data is too risky for a man-ufacturer to grant a supplier. ...
Reduced cerebral blood flow after severe head injury results in an increased risk of ischemic bra... more Reduced cerebral blood flow after severe head injury results in an increased risk of ischemic brain damage. Blood flow should therefore be monitored with a simple, reliable method. Transcranial color-coded Doppler sonography (TCCS) is an accepted tool for the diagnosis of cerebral vasospasm; however, its usefulness in evaluating patients with head injury has not been proven. Cerebral blood-flow velocity in the middle, anterior, and posterior cerebral arteries was measured with a 2.5 MHz probe (Aplio SSA 770A, Toshiba, Japan) in 36 subjects with moderate or severe head injury. Serial measurements of resistance index (RI), peak-systolic, end-diastolic, and mean velocity in the middle cerebral arteries were performed 2-24 h after head trauma and in the subsequent days during hospitalization. Immediately after head trauma, increased RI values, and unusually decreased blood-flow velocity (mainly in MCA) were observed. Microcirculation disturbances were suspected because the end-diastolic velocity had substantially diminished. Changes in blood-flow parameters correlated with the clinical state, and in most cases, a poor prognosis. In some patients, blood-flow velocity increased above the normal reference limit and this implied poor prognosis. Transcranial color-coded Doppler sonography is a reliable, repeatable, and accessible tool that provides information about cerebral blood-flow disturbances and may hold diagnostic and prognostic importance.
This study presents a method for computing a probabilistic atlas that describes the spatial distr... more This study presents a method for computing a probabilistic atlas that describes the spatial distributions of acute infarcts of the brain. The data consisted of diffusion-weighted-images (DWI) and high-resolution T1-weighted MR images representing 22 studies from 22 subjects. All DWI data sets contained high-intensity lesions on B-1000 maps, known from clinical history to be related to acute stroke. To compute the atlas, manually segmented infarcts on original DWI were spatially transformed and registered to a common coordinate system. This coordinate system allowed combining all lesions into a statistical atlas in the model space. As a result, the computed probabilistic map showed mild left-sided predominance of brain infarcts, which likely represents asymmetry in eloquence of brain regions. In our opinion, the statistical atlas of acute brain infarcts can facilitate computer-based detection of stroke in large image data sets.
BACKGROUND AND PURPOSE: Diffusion tensor imaging (DTI) allows direct visualization and volumetric... more BACKGROUND AND PURPOSE: Diffusion tensor imaging (DTI) allows direct visualization and volumetric analysis of the corticospinal tract (CST). The purpose of this study was to determine whether color maps and fiber tracking derived from DTI data are valuable in detecting and quantifying CST degen- eration in patients with amyotrophic lateral sclerosis (ALS). METHODS: Sixteen patients with ALS with clinical signs of upper motor neuron (UMN) involvement and 17 healthy subjects were studied with the use of DTI. Disease severity was determined by means of the ALS Functional Rating Scale-Revised (ALSFRS-R) and an UMN involvement score. DTI was acquired with a 12-direction, single-shot, spin-echo echo-planar sequence. The CST from the lower pons to the corona radiata at the level of the corpus callosum on 4 contiguous coronal sections was manually segmented by using color maps generated from the DTI data. The left and right CST volumes were measured separately and normalized to the total in...
We propose a new method for deformable registration of pre-operative and post-recurrence brain MR... more We propose a new method for deformable registration of pre-operative and post-recurrence brain MR scans of glioma patients. Performing this type of intra-subject registration is challenging as tumor, resection, recurrence, and edema cause large deformations, missing correspondences, and inconsistent intensity profiles between the scans. To address this challenging task, our method, called PORTR, explicitly accounts for pathological information. It segments tumor, resection cavity, and recurrence based on models specific to each scan. PORTR then uses the resulting maps to exclude pathological regions from the image-based correspondence term while simultaneously measuring the overlap between the aligned tumor and resection cavity. Embedded into a symmetric registration framework, we determine the optimal solution by taking advantage of both discrete and continuous search methods. We apply our method to scans of 24 glioma patients. Both quantitative and qualitative analysis of the results clearly show that our method is superior to other state-of-the-art approaches.
ABSTRACT Linear and nonlinear adaptive filtering algorithms are described, along with application... more ABSTRACT Linear and nonlinear adaptive filtering algorithms are described, along with applications to signal processing and control problems such as prediction, modeling, inverse modeling, equalization, echo cancelling, noise cancelling, and inverse control.
Evaluating various algorithms for the inter-subject registration of brain magnetic resonance imag... more Evaluating various algorithms for the inter-subject registration of brain magnetic resonance images (MRI) is a necessary topic receiving growing attention. Existing studies evaluated image registration algorithms in specific tasks or using specific databases (e.g., only for skull-stripped images, only for single-site images, etc.). Consequently, the choice of registration algorithms seems task- and usage/parameter-dependent. Nevertheless, recent large-scale, often multi-institutional imaging-related studies create the need and raise the question whether some registration algorithms can 1) generally apply to various tasks/databases posing various challenges; 2) perform consistently well, and while doing so, 3) require minimal or ideally no parameter tuning. In seeking answers to this question, we evaluated 12 general-purpose registration algorithms, for their generality, accuracy and robustness. We fixed their parameters at values suggested by algorithm developers as reported in the literature. We tested them in 7 databases/tasks, which present one or more of 4 commonly-encountered challenges: 1) inter-subject anatomical variability in skull-stripped images; 2) intensity homogeneity, noise and large structural differences in raw images; 3) imaging protocol and field-of-view (FOV) differences in multi-site data; and 4) missing correspondences in pathology-bearing images. Totally 7,562 registrations were performed. Registration accuracies were measured by (multi-)expert-annotated landmarks or regions of interest (ROIs). To ensure reproducibility, we used public software tools, public databases (whenever possible), and we fully disclose the parameter settings. We show evaluation results, and discuss the performances in light of algorithms' similarity metrics, transformation models and optimization strategies. We also discuss future directions for the algorithm development and evaluations.
To augment the analysis of dynamic susceptibility contrast material-enhanced magnetic resonance (... more To augment the analysis of dynamic susceptibility contrast material-enhanced magnetic resonance (MR) images to uncover unique tissue characteristics that could potentially facilitate treatment planning through a better understanding of the peritumoral region in patients with glioblastoma. Institutional review board approval was obtained for this study, with waiver of informed consent for retrospective review of medical records. Dynamic susceptibility contrast-enhanced MR imaging data were obtained for 79 patients, and principal component analysis was applied to the perfusion signal intensity. The first six principal components were sufficient to characterize more than 99% of variance in the temporal dynamics of blood perfusion in all regions of interest. The principal components were subsequently used in conjunction with a support vector machine classifier to create a map of heterogeneity within the peritumoral region, and the variance of this map served as the heterogeneity score. ...
... Proc AMIA Annu Fall Symp. 1997: 896. PMCID: PMC2233418. Copyright notice. A Textual Informati... more ... Proc AMIA Annu Fall Symp. 1997: 896. PMCID: PMC2233418. Copyright notice. A Textual Information Detection and Elimination System for Secure Medical Image Distribution *. James Ze Wang, Michel Bilello, and Gio Wiederhold. ...
The TIHI project addresses the issues that arise when some information must be shared among colla... more The TIHI project addresses the issues that arise when some information must be shared among collaborating, but distinct enterprises. Such enterprises cannot fully share their data and information resources, although some information exchange is essential. ...
Page 1. Protecting Collaboration Gio Wiederholdi Stanford University, CA Michel Bilello Stanford ... more Page 1. Protecting Collaboration Gio Wiederholdi Stanford University, CA Michel Bilello Stanford University, CA ... 1 Page 2. the acceptance of this approach 3 . Uncontrolled sharing of proprietary data is too risky for a man-ufacturer to grant a supplier. ...
Reduced cerebral blood flow after severe head injury results in an increased risk of ischemic bra... more Reduced cerebral blood flow after severe head injury results in an increased risk of ischemic brain damage. Blood flow should therefore be monitored with a simple, reliable method. Transcranial color-coded Doppler sonography (TCCS) is an accepted tool for the diagnosis of cerebral vasospasm; however, its usefulness in evaluating patients with head injury has not been proven. Cerebral blood-flow velocity in the middle, anterior, and posterior cerebral arteries was measured with a 2.5 MHz probe (Aplio SSA 770A, Toshiba, Japan) in 36 subjects with moderate or severe head injury. Serial measurements of resistance index (RI), peak-systolic, end-diastolic, and mean velocity in the middle cerebral arteries were performed 2-24 h after head trauma and in the subsequent days during hospitalization. Immediately after head trauma, increased RI values, and unusually decreased blood-flow velocity (mainly in MCA) were observed. Microcirculation disturbances were suspected because the end-diastolic velocity had substantially diminished. Changes in blood-flow parameters correlated with the clinical state, and in most cases, a poor prognosis. In some patients, blood-flow velocity increased above the normal reference limit and this implied poor prognosis. Transcranial color-coded Doppler sonography is a reliable, repeatable, and accessible tool that provides information about cerebral blood-flow disturbances and may hold diagnostic and prognostic importance.
This study presents a method for computing a probabilistic atlas that describes the spatial distr... more This study presents a method for computing a probabilistic atlas that describes the spatial distributions of acute infarcts of the brain. The data consisted of diffusion-weighted-images (DWI) and high-resolution T1-weighted MR images representing 22 studies from 22 subjects. All DWI data sets contained high-intensity lesions on B-1000 maps, known from clinical history to be related to acute stroke. To compute the atlas, manually segmented infarcts on original DWI were spatially transformed and registered to a common coordinate system. This coordinate system allowed combining all lesions into a statistical atlas in the model space. As a result, the computed probabilistic map showed mild left-sided predominance of brain infarcts, which likely represents asymmetry in eloquence of brain regions. In our opinion, the statistical atlas of acute brain infarcts can facilitate computer-based detection of stroke in large image data sets.
BACKGROUND AND PURPOSE: Diffusion tensor imaging (DTI) allows direct visualization and volumetric... more BACKGROUND AND PURPOSE: Diffusion tensor imaging (DTI) allows direct visualization and volumetric analysis of the corticospinal tract (CST). The purpose of this study was to determine whether color maps and fiber tracking derived from DTI data are valuable in detecting and quantifying CST degen- eration in patients with amyotrophic lateral sclerosis (ALS). METHODS: Sixteen patients with ALS with clinical signs of upper motor neuron (UMN) involvement and 17 healthy subjects were studied with the use of DTI. Disease severity was determined by means of the ALS Functional Rating Scale-Revised (ALSFRS-R) and an UMN involvement score. DTI was acquired with a 12-direction, single-shot, spin-echo echo-planar sequence. The CST from the lower pons to the corona radiata at the level of the corpus callosum on 4 contiguous coronal sections was manually segmented by using color maps generated from the DTI data. The left and right CST volumes were measured separately and normalized to the total in...
We propose a new method for deformable registration of pre-operative and post-recurrence brain MR... more We propose a new method for deformable registration of pre-operative and post-recurrence brain MR scans of glioma patients. Performing this type of intra-subject registration is challenging as tumor, resection, recurrence, and edema cause large deformations, missing correspondences, and inconsistent intensity profiles between the scans. To address this challenging task, our method, called PORTR, explicitly accounts for pathological information. It segments tumor, resection cavity, and recurrence based on models specific to each scan. PORTR then uses the resulting maps to exclude pathological regions from the image-based correspondence term while simultaneously measuring the overlap between the aligned tumor and resection cavity. Embedded into a symmetric registration framework, we determine the optimal solution by taking advantage of both discrete and continuous search methods. We apply our method to scans of 24 glioma patients. Both quantitative and qualitative analysis of the results clearly show that our method is superior to other state-of-the-art approaches.
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