Contributions

Papers
Conference Proceedings
Abstracts
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Abouhawwash, Alessio, “Multi-objective Optimization of Machine Learned Objective Functions for PET Image Reconstruction,” Journal of Nuclear Medicine (abstract), 2022.
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Alessio, Khan, and Patel, A multi-modal deep learning model integrates clinical, pathomic, and radiomic features for glioma classification and grading. Journal of Clinical Oncology 40:16_suppl, e14038-e14038, 2022.
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Gadgeel, Burkow, Perez, Junewick, Zbojniewicz, Otjen, Alessio, “Evaluation of inter-reader reproducibility for detection and labeling of pediatric rib fractures on radiographs,” International Pediatric Radiology Congress, Rome [Virtual], Oct 11-15, 2021.
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Burkow, Holste, Perez, Junewick, Zbojniewicz, Frost, Romberg, Menashe, Otjen, Alessio, "Rib Fracture Detection in Pediatric Radiographs via Deep Convolutional Neural Networks," International Pediatric Radiology Congress, Rome [Virtual], Oct 11-15, 2021.
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Mccandless, Alessio, Morrison, “Machine Learning to Predict the Risk of Pneumothorax Requiring Chest Tube Placement after Lung Biopsy,” 2021.
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Abouhawwash, Alessio, “Reference Point Based Genetic Algorithm for PET Image Reconstruction,” IEEE Nucl. Sci. Symp. and Med. Imaging Conf., Virtual, 2020.
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Azmat, Branch, Alessio, Virtual Clinical Trial to Evaluate the Benefit of Patient-Specific Blood Flow in CT Assessment of Functional Significance of Coronary Artery Stenosis, Biomedical Engineering Society (BMES) Annual Meeting, 2020.
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Tu, Brusen, Branch, Alessio, Comparison of Cardiac CT to PET for Non-invasive Myocardial Ischemia Grading, Biomedical Engineering Society (BMES) Annual Meeting, 2020.
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Abouhawwash, Deb, Alessio, “Exploration of Multi-objective Optimization with Genetic Algorithms for PET Image Reconstruction,” Journal of Nuclear Medicine (abstract), 2020.
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Alessio, Adams, Lassen, Slomka, “Characterization of Partial Volume Errors in Coronary Plaque PET Imaging,” Journal of Nuclear Medicine (abstract), 2020.
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Rubin, Adams, Cox, Pereira, Dighe, Alessio, “Machine learning with ultrasound to automate risk stratification and reduce fine needle aspiration in thyroid cancer” [Abstract 473]. 31(3):S209, 2020.
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Rubin, Adams, Cox, Pereira, Dighe, Wolf, and Alessio, “Towards automated structed reporting of thyroid ultrasound to reduce fine needle aspirations in thyroid cancer,” Michigan Osteopathic Association Annual Meeting, Grand Rapids, MI, 2019.
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Carras, Alessio, "Automatic Machine Learning Architecture Selection for Breast MRI Classification," MID-SURE Symposium, East Lansing, MI, 2019.
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Cox, Pereira, Dighe, Alessio, "Adaptation of the ResNet-50 Classification Architecture for the Prediction of Malignancy of Thyroid Nodules," MID-SURE Symposium, East Lansing, MI, 2019.
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Adams, Pereira, Dighe, Cox, Rubin, Alessio, "Classification of Thyroid Nodules using Machine Learned One Class Autoencoders," MID-SURE Symposium, East Lansing, MI, 2019.
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Sullivan, Holste, Alessio, "Deep Learning Methods for Automatic Evaluation of Lines in Chest Radiographs," MID-SURE Symposium, East Lansing, MI, 2019.
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Holste, Sullivan, Nagy, Bindschadler, Alessio, "Automatic Segmentation of Chest Radiographs with Deep Learning," MID-SURE Symposium, East Lansing, MI, 2019.
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Bindschadler, , Ferguson, Blackledge, Friedman, Otto, “Phantom for optimizing flow protocols in pediatric cardiac MRI,” Society for Cardiovascular Magnetic Resonance, Bellevue, 2019.
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Toia GV, Alessio AM, Mileto A. “Development of a Nonlinear Algorithm to Identify Minimal Detectable Concentrations of Trace Metals (Iron, Copper, Zinc) Using Dual-Energy CT in a Simulated Abdominal Phantom Experiment,” Society of Computed Body Tomography and Magnetic Resonance, Washington DC, 2018.