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Walter A. Hall

Researcher at State University of New York Upstate Medical University

Publications -  222
Citations -  8128

Walter A. Hall is an academic researcher from State University of New York Upstate Medical University. The author has contributed to research in topics: Magnetic resonance imaging & Immunotoxin. The author has an hindex of 48, co-authored 220 publications receiving 7796 citations. Previous affiliations of Walter A. Hall include State University of New York System & University of Minnesota.

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Book ChapterDOI

A Generic Framework for Non-rigid Registration Based on Non-uniform Multi-level Free-Form Deformations

TL;DR: This work combines multi-resolution optimization with free-form deformations based on multi-level B-splines to simulate a non-uniform control point distribution and demonstrates that the new algorithm can successfully register images with an improved performance, while achieving a significant reduction in run-time.
Journal ArticleDOI

Chemotherapy delivery issues in central nervous system malignancy: a reality check.

TL;DR: Because of the difficulty in treating CNS tumors, innovative treatments and alternative delivery techniques involving brain/cord capillaries, choroid plexus, and CSF are needed.
Journal ArticleDOI

Postoperative Central Nervous System Infection: Incidence and Associated Factors in 2111 Neurosurgical Procedures

TL;DR: The results from this study indicate that the true incidence of PCNSI after neurosurgical procedures may be greatly overestimated in the literature and that, in surgical procedures associated with a high risk of infection, prophylaxis for S. aureus and/or P. acnes infection should be of primary concern.
Journal ArticleDOI

Safety, efficacy, and functionality of high-field strength interventional magnetic resonance imaging for neurosurgery.

TL;DR: High-field (1.5-T) interventional MRI is a safe and effective technology for assisting neurosurgeons in achieving the goals of surgery and preliminary results suggest that the functional capabilities of this technology can yield data that can significantly influence intraoperative neurosurgical decision-making.