Brigham and Women's Hospital-ko ikertzaileekin lankidetzan egindako argitalpenak (22)

2022

  1. Application of a novel microscopic technique for quantifying CA125 binding to circulating mononuclear cells in longitudinal specimens during treatment for ovarian cancer

    Journal of Ovarian Research, Vol. 15, Núm. 1

2021

  1. Characterization of cell-bound ca125 on immune cell subtypes of ovarian cancer patients using a novel imaging platform

    Cancers, Vol. 13, Núm. 9

2020

  1. Biomarker Localization from Deep Learning Regression Networks

    IEEE Transactions on Medical Imaging, Vol. 39, Núm. 6, pp. 2121-2132

  2. Plasmonic Nanoparticle-Based Digital Cytometry to Quantify MUC16 Binding on the Surface of Leukocytes in Ovarian Cancer

    ACS Sensors, Vol. 5, Núm. 9, pp. 2772-2782

2019

  1. Localizing image-based biomarker regression without training masks: A new approach to biomarker discovery

    Proceedings - International Symposium on Biomedical Imaging

  2. Quantification of low abundance white cell surface molecules in ovarian cancer by dark field and fluorescence microscopy

    Bio-Optics: Design and Application - Proceedings Biophotonics Congress: Optics in the Life Sciences Congress 2019 (BODA, BRAIN, NTM, OMA, OMP)

  3. Quantification of low abundance white cell surface molecules in ovarian cancer by dark field and fluorescence microscopy

    Optics InfoBase Conference Papers

2018

  1. Automated Agatston score computation in non-ECG gated CT scans using deep learning

    Progress in Biomedical Optics and Imaging - Proceedings of SPIE

  2. Deep learning for biomarker regression: Application to osteoporosis and emphysema on chest CT scans

    Progress in Biomedical Optics and Imaging - Proceedings of SPIE

  3. Disease staging and prognosis in smokers using deep learning in chest computed tomography

    American Journal of Respiratory and Critical Care Medicine, Vol. 197, Núm. 2, pp. 193-203

  4. Multi-structure segmentation from partially labeled datasets. Application to body composition measurements on CT scans

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

  5. Multiorgan structures detection using deep convolutional neural networks

    Progress in Biomedical Optics and Imaging - Proceedings of SPIE

  6. On the relevance of the loss function in the agatston score regression from non-ECG gated CT scans

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

  7. Reply to Mummadi et al.

    American Journal of Respiratory and Critical Care Medicine

2017

  1. Highly sensitive and reliable plasmonic nanoparticle-based microscopy method for quantification of low abundance cell surface molecules

    Optics InfoBase Conference Papers

  2. Ventricular Geometry From Non-contrast Non-ECG-gated CT Scans: An Imaging Marker of Cardiopulmonary Disease in Smokers

    Academic Radiology, Vol. 24, Núm. 5, pp. 594-602

2016

  1. Automated Agatston score computation in a large dataset of non ECG-gated chest computed tomography

    Proceedings - International Symposium on Biomedical Imaging

  2. Computer vision profiling of neurite outgrowth dynamics reveals spatiotemporal modularity of Rho GTPase signaling

    Journal of Cell Biology, Vol. 212, Núm. 1, pp. 91-111

  3. Implementation and performance of automated software for computing right-to-left ventricular diameter ratio from computed tomography pulmonary angiography images

    Journal of Computer Assisted Tomography, Vol. 40, Núm. 3, pp. 387-392

  4. Pulmonary vascular morphology as an imaging biomarker in chronic thromboembolic pulmonary hypertension

    Pulmonary Circulation, Vol. 6, Núm. 1, pp. 70-81