Dr. Evan C. Harvey Profile

Dr. Evan C. Harvey

Research Assistant at Univ of Wisconsin

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Publications (3)

SPIE Journal Paper | 22 December 2020

Leveraging non-contrast head CT to improve the image quality of cerebral CT perfusion maps

Evan Harvey, Ke Li

JMI, Vol. 7, Issue 06, 063504, (December 2020) https://doi.org/10.1117/12.10.1117/1.JMI.7.6.063504

KEYWORDS: Computed tomography, Image quality, Image fusion, Tissues, Head, Denoising, Brain mapping, Lithium, Brain, Image processing

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Proceedings Article | 16 March 2020 Paper

Non-contrast head CT-assisted cerebral CT perfusion imaging

Evan Harvey, Ke Li

Proceedings Volume 11312, 1131236 (2020) https://doi.org/10.1117/12.2549712

KEYWORDS: Computed tomography, Head, Image quality, Tissues, Diagnostics, Brain, Deconvolution, Ischemic stroke, Blood, In vivo imaging

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Proceedings Article | 1 March 2019 Presentation + Paper

Impacts of photon counting detector to cerebral CT angiography maximum intensity projection (MIP) images

Evan Harvey, Mang Feng, Xu Ji, Ran Zhang, Guang-Hong Chen, Ke Li

Proceedings Volume 10948, 109481Z (2019) https://doi.org/10.1117/12.2513205

KEYWORDS: Signal to noise ratio, Computed tomography, Arteries, Sensors, Photon counting, Angiography, Signal detection, X-ray computed tomography, Spatial resolution, Head

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Cerebral CT angiography (CTA) is widely used for the diagnosis of various cerebrovascular diseases, including strokes, vasculitis, aneurysms, and etc.2–4 For the diagnosis of ischemic strokes, the availability of high quality CTA images not only helps in identifying the presence/location of large vessel occlusion but also facilitates the assessment of collateral blood supply. As another example, accurate rendering of the superficial temporal arteries is valuable in identifying vessel inflammations induced by giant cell arteritis.5 While CTA is an established clinical gold standard for imaging large cerebral arteries and veins,1 an important challenge that currently remains for MDCT-based CTA is its limited performance in imaging small perforating arteries with a diameter below 0.5 mm.4 As a consequence, the relativley invasive artery biopsy procedure remains the current clinical gold standard for the diagnosis of giant cell arteritis.6 The use of indirect conversion energy integrating detectors puts intrinsic limit on the spatial resolution of MDCT, both in-plane and along the z direction. Severe partial volume averaging effect (PVE) and the preferential weighting of high energy photons7 are among major reasons for the relatively poor performance of MDCT-based CTA for imaging iodinated small vessels. Photon counting detector-based CT (PCD-CT) offers potential technological solutions to these challenges MDCT systems face for CTA. When compared to MDCT, the direct conversion design of PCD reduces limitations on both in-plane and through-plane spatial resolution, and the inherent equal weighting of high and low energy photons of PCD-CT systems offers an improvement in the CNR of iodinated vessels. The purpose of this work was to theoretically and experimentally study the potential impacts of the PCD-CT technology to an important component of CTA image package: the maximum intensity projection (MIP) image. MIP is a simple 3D image visualization method to display CTA data sets. Based on source images alone, it can be very challenging to evaluate occlusion conditions since most vessels extend to different z positions. In comparison, a MIP image that extracted information from a much longer z range can provide clearer evidence for an occlusion; in addition, it can effectively enhance the visibility of small collateral vessels. This work first derived the statistical properties of the MIP image, then analyzed how each of the benefits of PCD (improved z resolution; reduced noise autocovariance along z) propagates from the source CT images to the final MIP image. Finally, experiments were performed using a benchtop PCD-CT system and an anthropomorphic CTA phantom to showcase the significantly improved visibility of small perforating arteries.

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