Assistant Professor of Biomedical Informatics

Assistant Professor of Radiology

Assistant Professor of Bioengineering

Contact Info:

Research Interests

Chapman's research interests focus on extracting desired information from volumetric and multispectral (multiple images of the same body region obtained with different contrast mechanisms) medical images.

Education

• MS, Electrical Engineering, University of Wisconsin
• PhD, Medical Informatics, University of Utah

Publications

Refereed Articles

Chapman BE, Minalga ES, Brown C, Roberts JA, Hadley JA. Reducing Morphological Variability of the Cervical Carotid Artery in Serial Magnetic Resonance Imaging Using a Head and Neck Immobilization Device. Magn Reson Imaging. 2008 Jul;28(1):258-62. PMID: 18581389

Zhang L, Chapman BE, Parker DL, Roberts JA, Guo J, Vemuri P, Moon S, Noo F. Automatic Detection of three-dimensional Vascular Tree Centerlines and Bifurcations in High-resolution MR Angiography. Invest Radiol. 2005 Oct;40(10):661-71. PMID: 16189435

Chapman BE, Parker DL. 3D multi-scale vessel enhancement filtering based on discrete estimates of maximum curvature differences: application time-of-flight MRA. Med Imag Anal 2005; 9(3): 191-208. PMID: 15854841

Christina Lee WC, Tublin ME, Chapman BE. Registration of MR and CT images of the liver: comparison of voxel similarity and surface based registration algorithms. Comput Methods Programs Biomed 2005; 78: 101-114. PMID: 5848266

Chapman BE, Yankelevitz DF, Henschke CI, Gur D. Lung cancer screening: simulations of effects of imperfect detection on temporal dynamics. Radiology 2005; 234:582-590. PMID: 15671008

Chapman WW, Fiszman M, Dowling JN, Chapman BE, Rindflesch TC. Identifying respiratory findings in emergency department reports for biosurveillance using MetaMap. Stud Health Technol Inform. 2004;107(Pt 1):487-91. PMID: 15360860

Mello-Thoms C, Chapman BE. A Preliminary Report on the Role of Spatial Frequency Analysis in the Perception of Breast Cancer Missed at Mammography Screening. Academic Radiology 2004; 11: 894-908. PMID: 15288040

Chapman BE, Parker DL, Stapelton JO. Intracranial vessel segmentation from time-of-flight MRA using pre-processing of the MIP Z-buffer: accuracy of the ZBS algorithm. Med Imag Anal 2004 Jun; 8(2): 113-126. PMID: 15063861

Chapman, BE, Stapelton JO, Tsuruda JS, Mello-Thoms C, Hamilton B. Katzman GL, Moore K. Parker DL. Diagnostic fidelity of the Z-buffer segmentation algorithm: preliminary assessment based on intracranial aneurysm detection. J Biomed Inform 2004 Feb; 37(1):19-29. PMID: 15016383

Leader JK, Zheng B, Rogers RM, Sciurba FC, Perez A, Chapman BE, Patel S, Fuhrman CR, Gur D. Automated lung segmentation in X-Ray computer Tomography: development and evaluation of a heuristic threshold-based scheme. Acad Radiol. 2003 Nov;10(11):1224-36. PMID: 14626297

Chapman WW, Cooper GF, Hanbury, P.,Chapman BE, Harrison LH, Wagner MM. Creating a text classifier to detect radiology reports describing mediastinal findings associated with inhalational anthrax and other disorders. JAMIA. 2003; Sep-Oct; 10(5):494-503. PMID: 12807805

Parker DL, Chapman BE, Goodrich KC, Roberts JA, Tsuruda JS, Katzman GL. The need for phase-encoding flow compensation in high resolution intracranial angiography. J Magn Reson Imaging. 2003 Jul;18(1):121-7. PMID: 12815647

Wang, XH, Good, WF, Chapman, BE, Chang YH, Poller WR, Chang, TS, Hardesty, LA. Automated assessment of the composition of breast tissue revealed on tissue-thickness-corrected mammography. AJR 2003; 180:257-262. PMID: 12490516

Chapman WW, Fiszman M, Chapman BE, Haug PJ. A comparison of classification algorithms to automatically identify chest x-ray reports that support pneumonia. JBI 2001 34(1):4-14, 2001.

Christian ME, Davidson HC, Wiggins RH 3rd, Berges G, Cannon G, Jackson G, Chapman B, Harnsberger HR. Digital processing of radiographic images from PACS to publishing. Journal of Digital Imaging. 14(1):14-7, 2001 Mar.

Chapman WW, Fiszman M, Frederick PR, Chapman BE, Haug PJ. Quantifying the characteristics of unambiguous chest radiography reports in the context of pneumonia. Acad Radiol. 2001 Jan; 8(1):57-66.

Alexander AL, Chapman BE, Tsuruda JS, Parker DL. A Median Filter for 3D Fast Spin Echo Black Blood Images of Cerebral Vessels. Magn Reson Med 2000; 43:310-313.

Parker DL, Chapman BE, Roberts JA, Alexander AL. Enhanced Image Detail Using Continuity in the MIP Z-Buffer: Applications to Magnetic Resonance Angiography. JMRI 2000; 11:378-388.

Chapman BE, Goodrich KC, Alexander AL, Blatter DD, Parker DL. Evaluation of Measures of Image Quality for Intracranial Magnetic Resonance Angiography. Computers and Biomedical Research 1999; 32:530-556.

Hadley JR, Chapman BE, Roberts JA, Chapman DC, Goodrich KC, Buswell HR, Alexander AL, Tsuruda JS, Parker DL. A Three coil comparison for MR angiography. JMRI 2000; 11:458-468.

Alexander AL, Buswell HR, Sun Y, Chapman BE, Tsuruda JS, Parker DL. Intra-Cranial Black-Blood MR Angiography with High-Resolution 3D Fast Spin-Echo. Magn Reson Med 1998; 40:298-310.

Chapman BE, Sanderson AR, Goodrich KC, Alexander AL, Blatter DD, Parker DL. Observer Performance Methodologies for Evaluating Blood Vessel Visibility in MR Angiograms using Accurate Geometric Registration to High Resolution X-ray Angiograms. Magn Reson Med 1997; 37:519-529.

Zhang YS, Scharer JE, Chapman BE. Electron Cyclotron Wave Scattering by a Probe-Launched Ion Acoustic Wave. Physics of Fluids B 1993; 5:3887-3892.

Grants

R01 HL087119 (Chapman, B)
3/1/2008- 2/28/2011
Univ of Pittsburgh (NIH)
Automated Detection of Thromboembolic Disease in CT Images
This project tests the feasibility of using a CAD tool to automatically diagnose thromboembolic disease as manifested in volumetric pulmonary and peripheral CT angiography (CTA) and CT venography (CTV) images. We will construct a database of 450 CTA/V that were acquired to rule out thromboembolic disease, along with corresponding clinical data which will be used to establish the true disease state. We will develop a set of vascular analysis algorithms that will be applied to the CTA/V images to automatically extract a centerline model of the relevant vascular trees. Detailed morphological measurements of the vasculature will be made automatically using the centerline model. These measurements will form the input vector to a computer-aided detection (CAD) algorithms based on artificial neural networks. The CAD algorithms will be used to determine the presence of thrombus or emboli within the vascular trees. The efficacy of the CAD algorithms will be assessed using FROC methods. Performance level of the CAD algorithms will be compared to the clinical radiologists’ interpretations of the performance experiment.

R01 HL057990 (Parker, D)
3/1/06-2/28/10
Univ of Utah (NIH)
High Resolution Cervical Carotid Imaging with MR
This project focused on developing and validating techniques for creating repeatable cervical carotid images with MRA/MRI. Using a head and neck immobilization device integrated with dedicated phased array coils designed specifically for imaging the carotid bulb, we acquired repeated images of individuals both with and without disease. Measures of changes in lumen and plaque morphology were made and the degree of variability observed was compared to that seen in repeated imaging without the immobilization device. Both intra- and inter-institution variability were measured.
Role: Co-Investigator

DAMD 17 03 2 0017 (Grzybicki, D)
9/15/06-3/15/08
Univ of Pittsburgh Medical Center (DOD)
IMITS Strategic Support of Telepathology Development in the Air Force
The focus of this proposal is on the implementation and evaluation of prototype telemedicine systems and clinical telemedicine applications. The technical objective of this project is to design, build and test a distributed radiology dynamic workload allocation telemedicine infrastructure prototype on a common technology platform. This system will provide widely available, flexible, clinically relevant services on a secure, stable low coat technology platform.

Lab Personnel

Yolanda DiBucci — Administrative Assistant
Alex Lisovich — Programmer
Doug Nielson — Student
Sean Lee — Student
Katherin Perperzak — Student
Xiuyun Shen — Programmer