Search Results - "GURCAN, N"

DeepFocus: Detection of out-of-focus regions in whole slide digital images using deep learning by Senaras, Caglar, Niazi, M Khalid Khan, Lozanski, Gerard, Gurcan, Metin N

“…The development of whole slide scanners has revolutionized the field of digital pathology. Unfortunately, whole slide scanners often produce images with…”
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Optimized generation of high-resolution phantom images using cGAN: Application to quantification of Ki67 breast cancer images by Senaras, Caglar, Niazi, Muhammad Khalid Khan, Sahiner, Berkman, Pennell, Michael P, Tozbikian, Gary, Lozanski, Gerard, Gurcan, Metin N

“…In pathology, Immunohistochemical staining (IHC) of tissue sections is regularly used to diagnose and grade malignant tumors. Typically, IHC stain…”
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Identifying tumor in pancreatic neuroendocrine neoplasms from Ki67 images using transfer learning by Niazi, Muhammad Khalid Khan, Tavolara, Thomas Erol, Arole, Vidya, Hartman, Douglas J, Pantanowitz, Liron, Gurcan, Metin N

“…The World Health Organization (WHO) has clear guidelines regarding the use of Ki67 index in defining the proliferative rate and assigning grade for pancreatic…”
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Content-Based Microscopic Image Retrieval System for Multi-Image Queries by Akakin, H. C., Gurcan, M. N.

“…In this paper, we describe the design and development of a multitiered content-based image retrieval (CBIR) system for microscopic images utilizing a reference…”
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OtoMatch: Content-based eardrum image retrieval using deep learning by Camalan, Seda, Niazi, Muhammad Khalid Khan, Moberly, Aaron C, Teknos, Theodoros, Essig, Garth, Elmaraghy, Charles, Taj-Schaal, Nazhat, Gurcan, Metin N

“…Acute infections of the middle ear are the most commonly treated childhood diseases. Because complications affect children's language learning and cognitive…”
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Histopathological Image Analysis: A Review by Gurcan, M.N., Boucheron, L.E., Can, A., Madabhushi, A., Rajpoot, N.M., Yener, B.

“…Over the past decade, dramatic increases in computational power and improvement in image analysis algorithms have allowed the development of powerful…”
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BCR-Net: A deep learning framework to predict breast cancer recurrence from histopathology images by Su, Ziyu, Niazi, Muhammad Khalid Khan, Tavolara, Thomas E, Niu, Shuo, Tozbikian, Gary H, Wesolowski, Robert, Gurcan, Metin N

“…Breast cancer is the most common malignancy in women, with over 40,000 deaths annually in the United States alone. Clinicians often rely on the breast cancer…”
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Computer-Aided Detection of Centroblasts for Follicular Lymphoma Grading Using Adaptive Likelihood-Based Cell Segmentation by Sertel, Olcay, Lozanski, Gerard, Shana'ah, Arwa, Gurcan, Metin N.

“…Follicular lymphoma (FL) is one of the most common lymphoid malignancies in the western world. FL has a variable clinical course, and important clinical…”
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Relationship between the Ki67 index and its area based approximation in breast cancer by Niazi, Muhammad Khalid Khan, Senaras, Caglar, Pennell, Michael, Arole, Vidya, Tozbikian, Gary, Gurcan, Metin N

“…The Ki67 Index has been extensively studied as a prognostic biomarker in breast cancer. However, its clinical adoption is largely hampered by the lack of a…”
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Value of Public Challenges for the Development of Pathology Deep Learning Algorithms by Hartman, Douglas Joseph, Van Der Laak, Jeroen A.W.M., Gurcan, Metin N., Pantanowitz, Liron

“…The introduction of digital pathology is changing the practice of diagnostic anatomic pathology. Digital pathology offers numerous advantages over using a…”
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Systems genetics uncover new loci containing functional gene candidates in Mycobacterium tuberculosis-infected Diversity Outbred mice by Gatti, Daniel M, Tyler, Anna L, Mahoney, J Matthew, Churchill, Gary A, Yener, Bulent, Koyuncu, Deniz, Gurcan, Metin N, Niazi, Mk Khalid, Tavolara, Thomas, Gower, Adam, Dayao, Denise, McGlone, Emily, Ginese, Melanie L, Specht, Aubrey, Alsharaydeh, Anas, Tessier, Philipe A, Kurtz, Sherry L, Elkins, Karen L, Kramnik, Igor, Beamer, Gillian

“…Mycobacterium tuberculosis infects two billion people across the globe, and results in 8-9 million new tuberculosis (TB) cases and 1-1.5 million deaths each…”
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Differential diagnosis of frontotemporal dementia subtypes with explainable deep learning on structural MRI by Ma, Da, Stocks, Jane, Rosen, Howard, Kantarci, Kejal, Lockhart, Samuel N, Bateman, James R, Craft, Suzanne, Gurcan, Metin N, Popuri, Karteek, Beg, Mirza Faisal, Wang, Lei

“…Frontotemporal dementia (FTD) represents a collection of neurobehavioral and neurocognitive syndromes that are associated with a significant degree of…”
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Utility of Polyethylene Terephthalate (Dacron) Vascular Grafts for Venous Outflow Reconstruction in Living-Donor Liver Transplantations by Arikan, T., Mammadov, E., Emek, E., Bozkurt, B., Inan Gurcan, N., Yazici, P., Sahin, T., Serin, A., Aydin, U., Tokat, Y.

“…Venous outflow reconstruction of modified right-lobe liver grafts has been shown to prevent the occurrence of graft congestion and subsequent complications,…”
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Deep learning predicts gene expression as an intermediate data modality to identify susceptibility patterns in Mycobacterium tuberculosis infected Diversity Outbred mice by Tavolara, Thomas E., Niazi, M.K.K., Gower, Adam C., Ginese, Melanie, Beamer, Gillian, Gurcan, Metin N.

“…Machine learning sustains successful application to many diagnostic and prognostic problems in computational histopathology. Yet, few efforts have been made to…”
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Translating prognostic quantification of c-MYC and BCL2 from tissue microarrays to whole slide images in diffuse large B-cell lymphoma using deep learning by Tavolara, Thomas E, Niazi, M Khalid Khan, Feldman, Andrew L, Jaye, David L, Flowers, Christopher, Cooper, Lee A D, Gurcan, Metin N

“…c-MYC and BCL2 positivity are important prognostic factors for diffuse large B-cell lymphoma. However, manual quantification is subject to significant intra-…”
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Dynamic 2-deoxy-D-glucose-enhanced multispectral optoacoustic tomography for assessing metabolism and vascular hemodynamics of breast cancer by Han, Zheng, MacCuaig, William M., Gurcan, Metin N., Claros-Sorto, Juan, Garwe, Tabitha, Henson, Christina, Holter-Chakrabarty, Jennifer, Hannafon, Bethany, Chandra, Vishal, Wellberg, Elizabeth, McNally, Lacey R.

“…Clinical tools for measuring tumor vascular hemodynamics, such as dynamic contrast-enhanced MRI, are clinically important to assess tumor properties. Here we…”
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Automatic discovery of clinically interpretable imaging biomarkers for Mycobacterium tuberculosis supersusceptibility using deep learning by Tavolara, Thomas E., Niazi, M. Khalid Khan, Ginese, Melanie, Piedra-Mora, Cesar, Gatti, Daniel M., Beamer, Gillian, Gurcan, Metin N.

“…Identifying which individuals will develop tuberculosis (TB) remains an unresolved problem due to few animal models and computational approaches that…”
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Nuclear IHC enumeration: A digital phantom to evaluate the performance of automated algorithms in digital pathology by Niazi, Muhammad Khalid Khan, Abas, Fazly Salleh, Senaras, Caglar, Pennell, Michael, Sahiner, Berkman, Chen, Weijie, Opfer, John, Hasserjian, Robert, Louissaint, Jr, Abner, Shana'ah, Arwa, Lozanski, Gerard, Gurcan, Metin N

“…Automatic and accurate detection of positive and negative nuclei from images of immunostained tissue biopsies is critical to the success of digital pathology…”
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Lung nodule detection on thoracic computed tomography images: Preliminary evaluation of a computer-aided diagnosis system by Gurcan, Metin N., Sahiner, Berkman, Petrick, Nicholas, Chan, Heang-Ping, Kazerooni, Ella A., Cascade, Philip N., Hadjiiski, Lubomir

“…We are developing a computer-aided diagnosis (CAD) system for lung nodule detection on thoracic helical computed tomography (CT) images. In the first stage of…”
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OtoPair: Combining Right and Left Eardrum Otoscopy Images to Improve the Accuracy of Automated Image Analysis by Camalan, Seda, Moberly, Aaron C., Teknos, Theodoros, Essig, Garth, Elmaraghy, Charles, Taj-Schaal, Nazhat, Gurcan, Metin N.

“…The accurate diagnosis of otitis media (OM) and other middle ear and eardrum abnormalities is difficult, even for experienced otologists. In our earlier…”
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