Michael D Ketcha
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Explore the profile of Michael D Ketcha including associated specialties, affiliations and a list of published articles.
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10
Citations
47
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Recent Articles
1.
Vijayan R, Han R, Wu P, Sheth N, Ketcha M, Vagdargi P, et al.
J Med Imaging (Bellingham)
. 2021 Jun;
8(3):035001.
PMID: 34124283
A method for fluoroscopic guidance of a robotic assistant is presented for instrument placement in pelvic trauma surgery. The solution uses fluoroscopic images acquired in standard clinical workflow and helps...
2.
Ketcha M, Marrama M, Souza A, Uneri A, Wu P, Zhang X, et al.
J Med Imaging (Bellingham)
. 2021 Mar;
8(5):052103.
PMID: 33732755
Cone-beam computed tomography (CBCT) is commonly used in the operating room to evaluate the placement of surgical implants in relation to critical anatomical structures. A particularly problematic setting, however, is...
3.
Zhang X, Uneri A, Wu P, Ketcha M, Jones C, Huang Y, et al.
Phys Med Biol
. 2021 Jan;
66(5):055008.
PMID: 33477120
Purpose: A system for long-length intraoperative imaging is reported based on longitudinal motion of an O-arm gantry featuring a multi-slot collimator. We assess the utility of long-length tomosynthesis and the...
4.
Doerr S, de Silva T, Vijayan R, Han R, Uneri A, Ketcha M, et al.
J Med Imaging (Bellingham)
. 2020 May;
7(3):035001.
PMID: 32411814
Measurement of global spinal alignment (GSA) is an important aspect of diagnosis and treatment evaluation for spinal deformity but is subject to a high level of inter-reader variability. Two methods...
5.
de Silva T, Vedula S, Perdomo-Pantoja A, Vijayan R, Doerr S, Uneri A, et al.
J Med Imaging (Bellingham)
. 2020 Feb;
7(3):031502.
PMID: 32090136
Data-intensive modeling could provide insight on the broad variability in outcomes in spine surgery. Previous studies were limited to analysis of demographic and clinical characteristics. We report an analytic framework...
6.
Ketcha M, de Silva T, Han R, Uneri A, Vogt S, Kleinszig G, et al.
J Med Imaging (Bellingham)
. 2019 Dec;
6(4):044008.
PMID: 31853461
Convolutional neural networks (CNNs) offer a promising means to achieve fast deformable image registration with accuracy comparable to conventional, physics-based methods. A persistent question with CNN methods, however, is whether...
7.
Ketcha M, de Silva T, Han R, Uneri A, Vogt S, Kleinszig G, et al.
IEEE Trans Med Imaging
. 2019 Apr;
38(9):2016-2027.
PMID: 30932834
Soft-tissue deformation presents a confounding factor to rigid image registration by introducing image content inconsistent with the underlying motion model, presenting non-correspondent structure with potentially high power, and creating local...
8.
de Silva T, Punnoose J, Uneri A, Mahesh M, Goerres J, Jacobson M, et al.
J Med Imaging (Bellingham)
. 2018 Mar;
5(1):015005.
PMID: 29487882
Positioning of an intraoperative C-arm to achieve clear visualization of a particular anatomical feature often involves repeated fluoroscopic views, which cost time and radiation exposure to both the patient and...
9.
Ketcha M, de Silva T, Han R, Uneri A, Goerres J, Jacobson M, et al.
IEEE Trans Med Imaging
. 2017 Jul;
36(10):1997-2009.
PMID: 28708549
For image-guided procedures, the imaging task is often tied to the registration of intraoperative and preoperative images to a common coordinate system. While the accuracy of this registration is a...
10.
de Silva T, Lo S, Aygun N, Aghion D, Boah A, Petteys R, et al.
Spine (Phila Pa 1976)
. 2016 Apr;
41(20):E1249-E1256.
PMID: 27035579
Study Design: An automatic radiographic labeling algorithm called "LevelCheck" was analyzed as a means of decision support for target localization in spine surgery. The potential clinical utility and scenarios in...