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255 results on '"Wyrwicz, Alice M."'

16. sj-pdf-1-asn-10.1177_1759091420922929 - Supplemental material for Diffusion Tensor Imaging Detects Acute and Subacute Changes in Corpus Callosum in Blast-Induced Traumatic Brain Injury

Author

Palamadai N. Venkatasubramanian, Prachi Keni, Gastfield, Roland, Limin Li, Aksenov, Daniil, Sherman, Sydney A., Bailes, Julian, Sindelar, Brian, Finan, John D., Lee, John, Bailes, Julian E., and Wyrwicz, Alice M.

Subjects
FOS: Clinical medicine, Medicine, 110904 Neurology and Neuromuscular Diseases
Abstract

Supplemental material, sj-pdf-1-asn-10.1177_1759091420922929 for Diffusion Tensor Imaging Detects Acute and Subacute Changes in Corpus Callosum in Blast-Induced Traumatic Brain Injury by Palamadai N. Venkatasubramanian, Prachi Keni, Roland Gastfield, Limin Li, Daniil Aksenov, Sydney A. Sherman, JulianBailes III Brian Sindelar, John D. Finan, John Lee, Julian E. Bailes and Alice M. Wyrwicz in ASN Neuro

Published
2020
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21. Diffusion Tensor Imaging Detects Acute and Subacute Changes in Corpus Callosum in Blast-Induced Traumatic Brain Injury

Author

Venkatasubramanian, Palamadai N., primary, Keni, Prachi, additional, Gastfield, Roland, additional, Li, Limin, additional, Aksenov, Daniil, additional, Sherman, Sydney A., additional, Bailes, Julian, additional, Sindelar, Brian, additional, Finan, John D., additional, Lee, John, additional, Bailes, Julian E., additional, and Wyrwicz, Alice M., additional

Published
2020
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29. Correlation of Placental Magnetic Resonance Imaging With Histopathologic Diagnosis: Detection of Aberrations in Structure and Water Diffusivity.

Author

Bockoven, Crystal, Gastfield, Roland D, Victor, Thomas, Venkatasubramanian, Palamadai N, Wyrwicz, Alice M, and Ernst, Linda M

Abstract

Objective: Noninvasive methods to identify placental pathologic conditions are being sought in order to recognize these conditions at an earlier stage leading to improved clinical interventions and perinatal outcomes. The objective of this study was to examine fixed tissue slices of placenta by T2- and diffusion-weighted magnetic resonance imaging (MRI) and correlate the images with placental pathologic findings defined by routine gross and histologic examination. Methods: Four formalin-fixed placentas with significant placental pathology (maternal vascular malperfusion, chronic villitis of unknown etiology, and massive perivillous fibrin deposition) and 2 histologically normal placentas were evaluated by high-resolution MRI. Representative placental slices were selected (2 cm long and 10 mm wide) and rehydrated. Imaging was performed on a Bruker Avance 14.1 T microimager. Diffusion-weighted images were acquired from 16 slices using slice thickness 0.5 mm and in-plane resolution approximately 100 µm × 100 µm. T2 maps were obtained from the same slices. T2 relaxation time and apparent diffusion coefficient (ADC) were acquired from representative regions of interest and compared between normal and diseased placentas. Results: In T2- and diffusion-weighted images, the placental microstructure differed subjectively between diseased and normal placentas. Furthermore, diseased placentas showed statistically significantly longer mean T2 relaxation times and generally higher mean ADC. Conclusion: Diffusion- and T2-weighted MRI can potentially be used to detect significant placental pathology by using T2 relaxation time and ADC as markers of altered placental microstructure. [ABSTRACT FROM AUTHOR]

Published
2020
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36. Automatic segmentation of amyloid plaques in MR images using unsupervised SVM

Author

Iordanescu, Gheorghe, Venkatasubramanian, Palamadai N., and Wyrwicz, Alice M.

Subjects
Mice, Support Vector Machine, Image Interpretation, Computer-Assisted, Animals, Brain, Reproducibility of Results, Mice, Transgenic, Plaque, Amyloid, Image Enhancement, Magnetic Resonance Imaging, Sensitivity and Specificity, Article, Algorithms
Abstract

Deposition of the β-amyloid peptide (Aβ) is an important pathological hallmark of Alzheimer's disease (AD). However, reliable quantification of amyloid plaques in both human and animal brains remains a challenge. We present here a novel automatic plaque segmentation algorithm based on the intrinsic MR signal characteristics of plaques. This algorithm identifies plaque candidates in MR data by using watershed transform, which extracts regions with low intensities completely surrounded by higher intensity neighbors. These candidates are classified as plaque or nonplaque by an unsupervised learning method using features derived from the MR data intensity. The algorithm performance is validated by comparison with histology. We also demonstrate the algorithm's ability to detect age-related changes in plaque load ex vivo in amyloid precursor protein (APP) transgenic mice that coexpress five familial AD mutations (5xFAD mice). To our knowledge, this study represents the first quantitative method for characterizing amyloid plaques in MRI data. The proposed method can be used to describe the spatiotemporal progression of amyloid deposition, which is necessary for understanding the evolution of plaque pathology in mouse models of Alzheimer's disease and to evaluate the efficacy of emergent amyloid-targeting therapies in preclinical trials.

Published
2011

40. Modularized architecture of address generation units suitable for real-time processing MR data on an FPGA.

Author

Limin Li and Wyrwicz, Alice M.

Subjects
*REAL-time computing, *FIELD programmable gate arrays, *ALGORITHMS, *MAGNETIC resonance imaging, *MODULAR design
Abstract

In this paper, we describe a modular approach to the design of an Address Generation Unit (AGU). The approach consists of development of a generic Address Generation Core (AGC) as a basic building block and the construction of an AGU from the AGCs. We illustrate this concept with AGUs capable of handling 2D- and 3D-structured data, and as well as their setup for executing 2D and 3D FFT algorithms on a Field Programmable Gate Array (FPGA). The AGUs developed using our proposed method are simple and easily expandable. Furthermore, they can potentially support irregularly structured data which are often generated from the wide variety of pulse sequences in magnetic resonance imaging. Our experimental results show that these AGUs are capable of generating addresses with a user-predefined pattern automatically at the speed of one address per clock cycle and operate at clock rates up to 80 MHz. They can operate concurrently with other processes and thus do not introduce additional operation latencies. Although we focus on applying the developed AGUs to executing 2D and 3D FFT, we expect that the modular design method should have much wider applications. [ABSTRACT FROM AUTHOR]

Published
2016
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42. Abstract 1499: Periprostatic fat from obese patients promotes prostate cancer growth

Author

Venkatasubramanian, Palamadai N., primary, Crawford, Susan E., additional, Fitchev, Philip S., additional, Brendler, Charles B., additional, Plunkett, Beth A., additional, Abroe, Betsy, additional, Mafi, Massa, additional, Morgan, Gina, additional, Cornwell, Mona L., additional, O'Leary, Judy, additional, Pruitt, Jacklyn, additional, Stadnik, Agnieszka, additional, Burright, Marna J., additional, McGuire, Michael S., additional, Wyrwicz, Alice M., additional, and Doll, Jennifer A., additional

Published
2012
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