The rapidly growing field of biomedical imaging enables one to visualize physiological structures, measure biological functions and evaluate cellular and molecular events without requiring invasive procedures. At the turn of the century, two engineers and a medical doctor, all interested in imaging, had a dream to develop a research environment that would forge the future of medical imaging at Case Western Reserve University. In 2005, the Case Center for Imaging Research (CCIR) was opened to fulfill that dream: to develop today what radiology and medical imaging will become in the next five to ten years. In 2012, imaging at CWRU BME was further bolstered by the opening of the Center for Computational Imaging and Personalized Diagnostics (CCIPD) with the goal of developing the analytic tools for quantitatively identifying and characterizing disease patterns on biomedical images.
Biomedical imaging research and development relies heavily on the many talents of Biomedical Engineers, a number of whom have established strong collaborations with a number of departments in the School of Medicine including radiology, urology, pathology, radiation oncology, and cardiology to name a few. The Department of Biomedical Engineering at Case Western Reserve University is a recognized national leader in biomedical imaging and our research programs serve as cornerstones for numerous interdisciplinary programs, including cancer diagnosis and prognosis, gene therapy, nanotechnology and drug delivery, cardiac physiology, and understanding of metabolic diseases. The BME research program aims to define medical imaging technology and applications that will be used both in the laboratory and in the clinical setting. Our BME Imaging Department provides a multifaceted program with strength in instrumentation and devices, computational algorithms, new imaging compounds, and novel clinical applications.To continually strive toward this goal, imaging research at Case Western Reserve University includes, but is not limited to: developing new imaging modalities and contrast agents that provide unprecedented spatial resolution and physiological and molecular details in the clinical setting; new computational imaging and pattern recognition algorithms to be able to identify subtle sub-visual cues that could enable predictions of disease behavior and progression; new hardware and computational algorithms that will lead to cutting edge developments in imaging quality, and using genetic information to develop new chemical compounds that reveal tumor margins or become active only in the presence of unique biological markers.
BME opportunities in imaging at CWRU span all of the major and emerging modalities, including magnetic resonance imaging and magnetic resonance fingerprinting, positron emission tomography, single photon emission computed tomography, ultrasound imaging, optical coherence tomography, computed tomography, digital radiography, digital pathology, bioluminescence imaging, fluorescence imaging, fluorescence molecular tomography, and other optical imaging methods including novel technologies such as cryo-imaging.
Applicable skills include: chemistry and polymer science, numerical methods and programming, image processing and machine learning, electronics, physics, optics, biomedical engineering, digital systems, physiology, cell and molecular biology, and/or design.
The imaging division of the Biomedical Engineering Department at Case Western Reserve University has a very strong track record of producing leading biomedical researchers both in academia and in industry and we are confident that our program will continue to lead imaging innovation well into the future. Please join us as we train the next generation of Biomedical Engineering leaders.
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High resolution imaging of endogenous gene expression; definition of "molecular signatures" for imaging and treatment of cancer and other diseases; generating and utilizing genomic data to define informative targets; strategies for applying non-invasive imaging to drug development; and novel molecular imaging probes and paradigms |
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Focuses on developing new technology and therapies for autonomic dysfunction, congenital heart defects, and opioid-induced disorders. Advancement categories: infrared neuromodulation, imaging, and drug development. |
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Efstathios (Stathis) Karathanasis, Ph.D. Cancer nanotechnology; Immunotherapy; Pediatric nanomedicine; Molecular imaging
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Machine Learning; AI in Imaging Centered Medical Data
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Drug delivery and molecular imaging; novel targeted imaging agents for molecular imaging; novel MRI contrast agents; image-guided therapy and drug delivery; polymeric drug delivery systems; multi-functional delivery systems for nucleic acids |
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Magnetic Resonance Imaging (MRI); Magnetic Resonance Fingerprinting ; Quantitative MR; MR Acquisition and Modeling;Neuroimaging
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Magnetic resonance imaging, Magnetic resonance fingerprinting, Inverse problems, Mathematical modeling
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Quantitative image analysis; Multi-modal, multi-scale correlation of massive data sets for disease diagnostics, prognostics, theragnostics: cancer applications.
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Biomedical optics; real-time in-vivo microstructural, functional, and molecular imaging using optical coherence tomography; diagnosis and guided therapy for cancer, cardiovascular, and ophthalmic disease
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Computerized decision support methods for evaluating disease presence and treatment response of radiotherapy and laser ablation therapy for neurological applications: brain tumors, epilepsy, and cancer pain. Novel automated algorithms to analyze and integrate multi-modal imaging data for disease diagnosis, prognosis, and treatment evaluation. |
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Medical image analysis, image radiomics, and machine learning schemes, focused on the use of post-processing, co-registration, and biological quantitation of imaging data. Applications in image-guided interventions, predictive guidance, and quantitative treatment response characterization in gastrointestinal cancers and inflammatory diseases. |
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Biomedical image processing; digital processing and quantitative image quality of X-ray fluoroscopy images; interventional MRI
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Magnetic resonance imaging and spectroscopy; Metabolic imaging; Diabetes, obesity and metabolic syndrome; Stroke; Blood-brain barrier; Glymphatic function; Cerebrovascular physiology; Neuroimaging; Cardiac MRI |
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Nanotechnology for Cancer Diagnosis and Treatment; Imaging and Manipulation of Tumor Microenvironment; Cancer Immunotherapy; Adoptive T cell Immunotherapy |
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Dr Janowczyk’s research focuses on applying machine learning and computer vision algorithms to digital pathology images. The resulting computational models aid pathologists in many common tasks, such as disease detection, grading, and the prediction of prognosis and therapy response. |
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Dr Lu’s research focuses on developing novel computational tools for identifying sub-visual image features from medical images and utilizing these features for disease classification, grading and prognosis in the context of breast cancer, head&neck cancer, and lung cancer.
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Building novel computational tools and machine learning models for characterization, diagnosis and prognosis of cancer on imaging.
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Exner, Agata A. |
University Hospitals phone: (216) 844-3544 |
Flask, Christopher |
University Hospitals phone: (216) 844-4963 |
Griswold, Mark |
University Hospitals phone: (216) 844-8085 |
Gulani, Vikas |
University Hospitals phone: (216) 844-3112 |
Jenkins, Michael |
University Hospitals email: michael.jenkins@case.edu |
Lee, Zhenghong |
University Hospitals phone: (216) 844-7920 |
Muzic, Raymond F. |
University Hospitals phone: (216) 844-3543 |