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Biblio

Found 24 results
2020
Lin P, Martel A, Camilleri S, Pop M. Co-registered Cardiac ex vivo DT Images and Histological Images for Fibrosis Quantification [Internet]. Pop M, Sermesant M, Camara O, Zhuang X, Li S, Young A, et al. Cham: Springer International Publishing; 2020. p. 3 - 11. http://link.springer.com/10.1007/978-3-030-39074-7_1
Niazi MKhalid Kha, Yazgan E, Tavolara TE, Li W, Lee CT, Parwani A, et al.. Semantic segmentation to identify bladder layers from H&E Images. Diagnostic Pathology. 2020 ;15:1–8.
Fauzi MFA, Chen W, Knight D, Hampel H, Frankel WL, Gurcan MN. Tumor Budding Detection System in Whole Slide Pathology Images. Journal of Medical Systems. 2020 ;44:1–10.
Hartman DJoseph, Van Der Laak JAWM, Gurcan MN, Pantanowitz L. Value of public challenges for the development of pathology deep learning algorithms. Journal of Pathology Informatics. 2020 ;11.
2019
Akbar S, Peikari M, Salama S, Panah AYazdan, Nofech-Mozes S, Martel AL. Automated and Manual Quantification of Tumour Cellularity in Digital Slides for Tumour Burden Assessment. Scientific Reports [Internet]. 2019 ;91530252824533575211327791(1521). http://www.nature.com/articles/s41598-019-50568-4
Kus P, Gurcan MN, Beamer G. Automatic Detection of Granuloma Necrosis in Pulmonary Tuberculosis Using a Two-Phase Algorithm: 2D-TB. Microorganisms. 2019 ;7:661.
Li X, Zhang S, Zhang Q, Wei X, Pan Y, Zhao J, et al.. Diagnosis of thyroid cancer using deep convolutional neural network models applied to sonographic images: a retrospective, multicohort, diagnostic study. The Lancet Oncology. 2019 ;20:193–201.
Niazi MKhalid Kha, Parwani AV, Gurcan MN. Digital pathology and artificial intelligence. The lancet oncology. 2019 ;20:e253–e261.
Tavolara TE, M Niazi KKhan, Arole V, Chen W, Frankel W, Gurcan MN. A modular cGAN classification framework: Application to colorectal tumor detection. Scientific reports. 2019 ;9:1–8.
M Niazi KKhan, Lin Y, Liu F, Ashok A, Marcellin MW, Tozbikian G, et al.. Pathological image compression for big data image analysis: Application to hotspot detection in breast cancer. Artificial intelligence in medicine. 2019 ;95:82–87.
2018
Senaras C, Gurcan MNafi. Deep learning for medical image analysis. Journal of pathology informatics. 2018 ;9.
Senaras C, M Niazi KKhan, Lozanski G, Gurcan MN. DeepFocus: detection of out-of-focus regions in whole slide digital images using deep learning. PloS one. 2018 ;13:e0205387.
Niazi MKhalid Kha, Tavolara TErol, Arole V, Hartman DJ, Pantanowitz L, Gurcan MN. Identifying tumor in pancreatic neuroendocrine neoplasms from Ki67 images using transfer learning. PloS one. 2018 ;13:e0195621.
Jordan J, Goldstein JS, Jaye DL, Gurcan M, Flowers CR, Cooper LAD. Informatics approaches to address new challenges in the classification of lymphoid malignancies. JCO clinical cancer informatics. 2018 ;2:1–9.
Niazi MKhalid Kha, Abas FSalleh, Senaras C, Pennell M, Sahiner B, Chen W, et al.. Nuclear IHC enumeration: A digital phantom to evaluate the performance of automated algorithms in digital pathology. PloS one. 2018 ;13:e0196547.
Senaras C, Niazi MKhalid Kha, Sahiner B, Pennell MP, Tozbikian G, Lozanski G, et al.. Optimized generation of high-resolution phantom images using cGAN: Application to quantification of Ki67 breast cancer images. PloS one. 2018 ;13:e0196846.
Niazi MKhalid Kha, Senaras C, Pennell M, Arole V, Tozbikian G, Gurcan MN. Relationship between the Ki67 index and its area based approximation in breast cancer. BMC cancer. 2018 ;18:1–9.
Wahid A‐, Cydzik M, Fischer NW, Prodeus A, Shively JE, Martel A, et al.. Serum-derived carcinoembryonic antigen (CEA) activates fibroblasts to induce a local re-modeling of the extracellular matrix that favors the engraftment of CEA-expressing tumor cells. International Journal of Cancer [Internet]. 2018 ;1433661(8):1963 - 1977. https://onlinelibrary.wiley.com/doi/10.1002/ijc.31586
2017
Peikari M, Salama S, Nofech-Mozes S, Martel AL. Automatic cellularity assessment from post-treated breast surgical specimens. Cytometry Part A [Internet]. 2017 ;91(11):1078 - 1087. http://doi.wiley.com/10.1002/cyto.a.v91.11
Gurcan MN, Tomaszewski J, Overton JA, Doyle S, Ruttenberg A, Smith B. Developing the Quantitative Histopathology Image Ontology (QHIO): A case study using the hot spot detection problem. Journal of Biomedical Informatics [Internet]. 2017 ;66:129 - 135. http://www.sciencedirect.com/science/article/pii/S1532046416301800
Martel AL, Hosseinzadeh D, Senaras C, Zhou Y, Yazdanpanah A, Shojaii R, et al.. An Image Analysis Resource for Cancer Research: PIIP—Pathology Image Informatics Platform for Visualization, Analysis, and Management. Cancer Research [Internet]. 2017 ;77(21):e83 - e86. http://cancerres.aacrjournals.org/content/77/21/e83
2016
Shojaii R, Martel AL. Optimized SIFTFlow for registration of whole-mount histology to reference optical images. Journal of Medical Imaging [Internet]. 2016 ;3(4). http://medicalimaging.spiedigitallibrary.org/article.aspx?articleid=2571703
2014
Shojaii R, Bacopulos S, Yang W, Karavardanyan T, Spyropoulos D, Raouf A, et al.. Reconstruction of 3-dimensional histology volume and its application to study mouse mammary glands. J Vis Exp. 2014 ;(89):e51325.
2012
Janowczyk A, Chandran S, Singh R, Sasaroli D, Coukos G, Feldman MD, et al.. High-throughput biomarker segmentation on ovarian cancer tissue microarrays via hierarchical normalized cuts. IEEE Trans Biomed Eng. 2012 ;59(5):1240-52.