Metin Nafi Gürcan

发表

An automated method for counting cytotoxic T-cells from CD8 stained images of renal biopsies

M. Khalid Khan, Anjali A. Satoskar, Metin Nafi Gürcan, 2013, Medical Imaging.

An Image Analysis Approach for Detecting Malignant Cells in Digitized H&E-stained Histology Images of Follicular Lymphoma

Metin Nafi Gürcan, Ümit V. Çatalyürek, Olcay Sertel, 2010, 2010 20th International Conference on Pattern Recognition.

Radiopathomics: Integration of radiographic and histologic characteristics for prognostication in glioblastoma pdf

Metin Nafi Gürcan, Saima Rathore, Muhammad Aksam Iftikhar, 2019, Neuro-Oncology.

Automatic detection of follicular regions in H&E images using iterative shape index

Metin Nafi Gürcan, Siddharth Samsi, Gerard Lozanski, 2011, Comput. Medical Imaging Graph..

Detection of eardrum abnormalities using ensemble deep learning approaches

Metin Nafi Gürcan, Çaglar Senaras, Aaron C. Moberly, 2018, Medical Imaging.

Computer-Aided Detection of Centroblasts for Follicular Lymphoma Grading Using Adaptive Likelihood-Based Cell Segmentation

Metin Nafi Gürcan, Olcay Sertel, Gerard Lozanski, 2010, IEEE Transactions on Biomedical Engineering.

Content-adaptive color transform for image compression

A. Enis Çetin, Metin Nafi Gürcan, Kivanç Köse, 2010, 2010 IEEE International Conference on Image Processing.

Computer-aided prognosis of neuroblastoma on whole-slide images: Classification of stromal development

Jun Kong, Joel H. Saltz, Metin Nafi Gürcan, 2009, Pattern Recognit..

Identifying bladder layers from H and E images using U-Net image segmentation

Metin Nafi Gürcan, Anil Parwani, Muhammad Khalid Khan Niazi, 2020, Medical Imaging: Digital Pathology.

Automated T1 bladder risk stratification based on depth of lamina propria invasion from H and E tissue biopsies: a deep learning approach

M. Khalid Khan, Metin Nafi Gürcan, Anil V. Parwani, 2018, Medical Imaging.

Image Analysis for Cystic Fibrosis: Computer-Assisted Airway Wall and Vessel Measurements from Low-Dose, Limited Scan Lung CT Images

Metin Nafi Gürcan, Ü. Erkan Mumcuoglu, Frederick R. Long, 2013, Journal of Digital Imaging.

Coordinating the use of GPU and CPU for improving performance of compute intensive applications

Metin Nafi Gürcan, Wagner Meira, Ümit V. Çatalyürek, 2009, 2009 IEEE International Conference on Cluster Computing and Workshops.

Performance vs. accuracy trade-offs for large-scale image analysis applications

Jun Kong, Joel H. Saltz, Metin Nafi Gürcan, 2007, 2007 IEEE International Conference on Cluster Computing.

Intraoperative neuropathology of glioma recurrence: cell detection and classification

Metin Nafi Gürcan, Fazly Salleh Abas, Hamza Numan Gokozan, 2016, SPIE Medical Imaging.

Quantification of liver fat: A comprehensive review

Metin Nafi Gürcan, Xia Jiang, Evgin Göçeri, 2016, Comput. Biol. Medicine.

Acne image analysis: lesion localization and classification

Metin Nafi Gürcan, Fazly Salleh Abas, Benjamin Kaffenberger, 2016, SPIE Medical Imaging.

Tumor microenvironment for follicular lymphoma: structural analysis for outcome prediction

Berkman Sahiner, Metin Nafi Gürcan, W. Chen, 2018, Medical Imaging.

Analysis of temporal change of mammographic features for computer-aided characterization of malignant and benign masses

Berkman Sahiner, Lubomir M. Hadjiiski, Heang-Ping Chan, 2001, SPIE Medical Imaging.

Characterizing primary refractory neuroblastoma: prediction of outcome by microscopic image analysis

M. Khalid Khan, Metin Nafi Gürcan, Daniel A. Weiser, 2015, Medical Imaging.

Measurement of colonic polyp size from virtual colonoscopy studies: comparison of manual and automated methods

Metin Nafi Gürcan, Aytekin Oto, Steve Rogers, 2006, SPIE Medical Imaging.

Developing the Quantitative Histopathology Image Ontology (QHIO): A case study using the hot spot detection problem

Metin Nafi Gürcan, Barry Smith, Alan Ruttenberg, 2017, J. Biomed. Informatics.

VirtualPACS—A Federating Gateway to Access Remote Image Data Resources over the Grid

Tony Pan, Joel H. Saltz, Metin Nafi Gürcan, 2009, Journal of Digital Imaging.

Temporal Analysis of Tumor Heterogeneity and Volume for Cervical Cancer Treatment Outcome Prediction: Preliminary Evaluation

Dongqing Zhang, Joel H. Saltz, Metin Nafi Gürcan, 2010, Journal of Digital Imaging.

IMAGE ANALYSIS FOR AUTOMATED ASSESSMENT OF GRADE OF NEUROBLASTIC DIFFERENTIATION

Kim L. Boyer, Joel H. Saltz, Metin Nafi Gürcan, 2007, 2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

Pattern Recognition in Histopathological Images: An ICPR 2010 Contest

Metin Nafi Gürcan, Nasir M. Rajpoot, Anant Madabhushi, 2010, ICPR Contests.

Autoscope: automated otoscopy image analysis to diagnose ear pathology and use of clinically motivated eardrum features

Metin Nafi Gürcan, Çaglar Senaras, Aaron C. Moberly, 2017, Medical Imaging.

Microcalcifications Detection Using Adaptive Filtering and Gaussianity Tests

A. Enis Çetin, Metin Nafi Gürcan, Yasemin Yardimci, 1998, Digital Mammography / IWDM.

Computer-assisted bladder cancer grading: α-shapes for color space decomposition

M. Khalid Khan, Metin Nafi Gürcan, Anil V. Parwani, 2016, SPIE Medical Imaging.

Histopathological Image Analysis Using Model-Based Intermediate Representations and Color Texture: Follicular Lymphoma Grading

Joel H. Saltz, Metin Nafi Gürcan, Ümit V. Çatalyürek, 2009, J. Signal Process. Syst..

Computer-aided characterization of mammographic masses: accuracy of mass segmentation and its effects on characterization

Berkman Sahiner, Lubomir M. Hadjiiski, Heang-Ping Chan, 2001, IEEE Transactions on Medical Imaging.

Microcalcification segmentation and mammogram image enhancement using nonlinear filtering

A. Enis Çetin, Metin Nafi Gürcan, Yasemin Yardimci, 1999, NSIP.

Computer-aided evaluation of neuroblastoma on whole-slide histology images: Classifying grade of neuroblastic differentiation

Kim L. Boyer, Jun Kong, Joel H. Saltz, 2009, Pattern Recognit..

Massively multithreaded maxflow for image segmentation on the Cray XMT‐2

Shahid H. Bokhari, Metin Nafi Gürcan, Ümit V. Çatalyürek, 2014, Concurr. Comput. Pract. Exp..

Computerized segmentation and measurement of chronic wound images

Metin Nafi Gürcan, Mohammad Faizal Ahmad Fauzi, Chandan K. Sen, 2015, Comput. Biol. Medicine.

Grading vascularity from histopathological images based on traveling salesman distance and vessel size

M. Khalid Khan, Metin Nafi Gürcan, Gerard Lozanski, 2014, Medical Imaging.

Stroma classification for neuroblastoma on graphics processors

Joel H. Saltz, Metin Nafi Gürcan, Antonio Ruiz, 2009, Int. J. Data Min. Bioinform..

Pathological Image Analysis Using the GPU: Stroma Classification for Neuroblastoma

Joel H. Saltz, Metin Nafi Gürcan, Antonio Ruiz, 2007, 2007 IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2007).

Content-Based Microscopic Image Retrieval System for Multi-Image Queries

Metin Nafi Gürcan, Hatice Çinar Akakin, M. Gürcan, 2012, IEEE Transactions on Information Technology in Biomedicine.

Influence function based Gaussianity tests for detection of microcalcifications in mammogram images

A. Enis Çetin, Metin Nafi Gürcan, Yasemin Yardimci, 1999, Proceedings 1999 International Conference on Image Processing (Cat. 99CH36348).

A Knowledge-Anchored Integrative Image Search and Retrieval System

Joel H. Saltz, Metin Nafi Gürcan, Ümit V. Çatalyürek, 2009, Journal of Digital Imaging.

Classification of follicular lymphoma: the effect of computer aid on pathologists grading

Berkman Sahiner, Metin Nafi Gürcan, Stephen M. Smith, 2015, BMC Medical Informatics and Decision Making.

Optimal neural network architecture selection: effects on computer-aided detection of mammographic microcalcifications

Berkman Sahiner, Lubomir M. Hadjiiski, Heang-Ping Chan, 2002, SPIE Medical Imaging.

Effect of pathologist agreement on evaluating a computer-aided assisted system: Recognizing centroblast cells in follicular lymphoma cases

Metin Nafi Gürcan, Gerard Lozanski, Arwa Shanaah, 2010, 2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

A computational framework to detect normal and tuberculosis infected lung from H and E-stained whole slide images

M. Khalid Khan, Metin Nafi Gürcan, Gillian Beamer, 2017, Medical Imaging.

Heterogeneity assessment of histological tissue sections in whole slide images

Metin Nafi Gürcan, Catherine Bor-Angelier, Benoît Plancoulaine, 2015, Comput. Medical Imaging Graph..

Segmentation and automated measurement of chronic wound images: probability map approach

Metin Nafi Gürcan, Mohammad Faizal Ahmad Fauzi, Chandan K. Sen, 2014, Medical Imaging.

Feature-based registration of histopathology images with different stains: An application for computerized follicular lymphoma prognosis

Jun Kong, Metin Nafi Gürcan, Lee A. D. Cooper, 2009, Comput. Methods Programs Biomed..

Generalization of tumor identification algorithms

Metin Nafi Gürcan, Çaglar Senaras, Vidya Arole, 2019, Medical Imaging.

Splitting touching-cell clusters on histopathological images

Hui Kong, Metin Nafi Gürcan, Kamel Belkacem-Boussaid, 2011, 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

Service-Based Access to and Processing of Large Scientific Datasets

Jun Kong, Tony Pan, Joel H. Saltz, 2006, High Performance Computing Workshop.

An analysis of methods for the selection of atlases for use in medical image segmentation

Metin Nafi Gürcan, Thomas M. Best, Jeffrey W. Prescott, 2010, Medical Imaging.

An efficient computational framework for the analysis of whole slide images: Application to follicular lymphoma immunohistochemistry

Metin Nafi Gürcan, Siddharth Samsi, Ashok K. Krishnamurthy, 2012, J. Comput. Sci..

Segmentation of follicles from CD8-stained slides of follicular lymphoma using deep learning

Berkman Sahiner, M. Khalid Khan, Metin Nafi Gürcan, 2019, Medical Imaging.

e-Science, caGrid, and Translational Biomedical Research

Tony Pan, Joel H. Saltz, Metin Nafi Gürcan, 2008, Computer.

Follicular lymphoma grading using cell-graphs and multi-scale feature analysis

Hui Kong, Metin Nafi Gürcan, Bülent Yener, 2012, Medical Imaging.

An application of transfer learning to neutrophil cluster detection for tuberculosis: efficient implementation with nonmetric multidimensional scaling and sampling

M. Khalid Khan, Metin Nafi Gürcan, Gillian Beamer, 2018, Medical Imaging.

Texture classification using nonlinear color quantization: Application to histopathological image analysis

Jun Kong, Joel H. Saltz, Metin Nafi Gürcan, 2008, 2008 IEEE International Conference on Acoustics, Speech and Signal Processing.

Hotspot detection in pancreatic neuroendocrine images using local depth

Metin Nafi Gürcan, Kenneth S. Berenhaut, Muhammad Khalid Khan Niazi, 2020, Medical Imaging: Digital Pathology.

Fully automated liver segmentation from SPIR image series

Metin Nafi Gürcan, Oguz Dicle, Evgin Göçeri, 2014, Comput. Biol. Medicine.

Computerized classification of intraductal breast lesions using histopathological images

Metin Nafi Gürcan, Murat Dundar, Gökhan Bilgin, 2011, IEEE Transactions on Biomedical Engineering.

Computerized lung nodule detection on thoracic CT images: combined rule-based and statistical classifier for false-positive reduction

Berkman Sahiner, Lubomir M. Hadjiiski, Heang-Ping Chan, 2001, SPIE Medical Imaging.

Microscopic image analysis for quantitative characterization of muscle fiber type composition

Metin Nafi Gürcan, Olcay Sertel, Belma Dogdas, 2011, Comput. Medical Imaging Graph..

Colorectal tumor identification by transferring knowledge from pan-cytokeratin to H&E

Metin Nafi Gürcan, Wei Chen, Muhammad Khalid Khan Niazi, 2019, Medical Imaging.

Processing of Large-Scale Biomedical Images on a Cluster of Multicore CPUs and GPUs

Joel H. Saltz, Metin Nafi Gürcan, Antonio Ruiz, 2008, High Performance Computing Workshop.

Template-based level set segmentation using anatomical information

Metin Nafi Gürcan, Kimerly Powell, Thomas M. Best, 2009, 2009 24th International Symposium on Computer and Information Sciences.

Nonlinear subband decomposition structures in GF-(N) arithmetic

A. Enis Çetin, Metin Nafi Gürcan, Ömer Nezih Gerek, 1998, Signal Process..

Segmentation of follicular regions on H&E slides using a matching filter and active contour model

Metin Nafi Gürcan, Gerard Lozanski, Kamel Belkacem-Boussaid, 2010, Medical Imaging.

Automatic graph-cut based segmentation of bones from knee magnetic resonance images for osteoarthritis research

Metin Nafi Gürcan, Sufyan Y. Ababneh, Jeffrey W. Prescott, 2011, Medical Image Anal..

An adaptive algorithm for detection of multiple-type, positively stained nuclei in IHC images with minimal prior information: application to OLIG2 staining gliomas

Metin Nafi Gürcan, Hatice Çinar Akakin, Jose J. Otero, 2015, Medical Imaging.

Computerized Pathological Image Analysis For Neuroblastoma Prognosis

Jun Kong, Joel H. Saltz, Metin Nafi Gürcan, 2007, AMIA.

Computer-aided prognosis of neuroblastoma: classification of stromal development on whole-slide images

Jun Kong, Joel H. Saltz, Metin Nafi Gürcan, 2008, SPIE Medical Imaging.

Computerized microscopic image analysis of follicular lymphoma

Jun Kong, Joel H. Saltz, Metin Nafi Gürcan, 2008, SPIE Medical Imaging.

Pixels to diagnosis: image analysis for digital pathology (Conference Presentation)

Metin Nafi Gürcan, 2019, Medical Imaging: Digital Pathology.

Partitioning Histopathological Images: An Integrated Framework for Supervised Color-Texture Segmentation and Cell Splitting

Hui Kong, Metin Nafi Gürcan, Kamel Belkacem-Boussaid, 2011, IEEE Transactions on Medical Imaging.

A multi-resolution image analysis system for computer-assisted grading of neuroblastoma differentiation

Kim L. Boyer, Jun Kong, Joel H. Saltz, 2008, SPIE Medical Imaging.

Use of joint two-view information for computerized lesion detection on mammograms: improvement of microcalcification detection accuracy

Berkman Sahiner, Lubomir M. Hadjiiski, Heang-Ping Chan, 2002, SPIE Medical Imaging.

Special issue on whole slide microscopic image processing

Metin Nafi Gürcan, Jean-Christophe Olivo-Marin, Olivier Lézoray, 2011, Comput. Medical Imaging Graph..

FOXP3-stained image analysis for follicular lymphoma: optimal adaptive thresholding with maximal nucleus coverage

Berkman Sahiner, Metin Nafi Gürcan, W. Chen, 2017, Medical Imaging.

Muscle histology image analysis for sarcopenia: Registration of successive sections with distinct atpase activity

Metin Nafi Gürcan, Olcay Sertel, Belma Dogdas, 2010, 2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

Visually Meaningful Histopathological Features for Automatic Grading of Prostate Cancer

M. Khalid Khan, Metin Nafi Gürcan, Mehmet Koyutürk, 2017, IEEE Journal of Biomedical and Health Informatics.

GridIMAGE: A Novel Use of Grid Computing to Support Interactive Human and Computer-Assisted Detection Decision Support

Tony Pan, Joel H. Saltz, Metin Nafi Gürcan, 2007, Journal of Digital Imaging.

A morphological subband decomposition structure using GF(N) arithmetic

A. Enis Çetin, Metin Nafi Gürcan, Ömer Nezih Gerek, 1996, Proceedings of 3rd IEEE International Conference on Image Processing.

Segmentation of mycobacterium tuberculosis bacilli clusters from acid-fast stained lung biopsies: a deep learning approach

Metin Nafi Gürcan, Muhammad Khalid Khan Niazi, Thomas E. Tavolara, 2020, Medical Imaging: Digital Pathology.

Pathological image compression for big data image analysis: Application to hotspot detection in breast cancer

Michael W. Marcellin, M. Khalid Khan, Metin Nafi Gürcan, 2019, Artif. Intell. Medicine.

Prognostic Reporting of p53 Expression by Image Analysis in Glioblastoma Patients: Detection and Classification

Metin Nafi Gürcan, Mohammad Faizal Ahmad Fauzi, Jose J. Otero, 2015, HIS.

Creating synthetic digital slides using conditional generative adversarial networks: application to Ki67 staining

Berkman Sahiner, Metin Nafi Gürcan, Gerard Lozanski, 2018, Medical Imaging.

Automated detection and enhancement of microcalcifications in mammograms using nonlinear subband decomposition

A. Enis Çetin, Metin Nafi Gürcan, Rashid Ansari, 1997, 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing.

Computer-aided characterization of malignant and benign microcalcification clusters based on the analysis of temporal change of mammographic features

Berkman Sahiner, Lubomir M. Hadjiiski, Heang-Ping Chan, 2002, SPIE Medical Imaging.

Adaptive Discriminant Wavelet Packet Transform and Local Binary Patterns for Meningioma Subtype Classification

Metin Nafi Gürcan, Nasir M. Rajpoot, Roland Wilson, 2008, MICCAI.

Automated detection of cells from immunohistochemically-stained tissues: application to Ki-67 nuclei staining

Hui Kong, Metin Nafi Gürcan, Hatice Çinar Akakin, 2012, Medical Imaging.

Cell nuclei segmentation for histopathological image analysis

Metin Nafi Gürcan, Hui Kong, Kamel Belkacem-Boussaid, 2011, Medical Imaging.

Entropy based quantification of Ki-67 positive cell images and its evaluation by a reader study

M. Khalid Khan, Metin Nafi Gürcan, Gerard Lozanski, 2013, Medical Imaging.

A Multiple Instance Learning Approach toward Optimal Classification of Pathology Slides

Metin Nafi Gürcan, Murat Dundar, Olcay Sertel, 2010, 2010 20th International Conference on Pattern Recognition.

Evolving strategies for the development and evaluation of a computerised melanoma image analysis system

Metin Nafi Gürcan, M. Emre Celebi, M. E. Celebi, 2018, Comput. methods Biomech. Biomed. Eng. Imaging Vis..

Detection of Follicles From IHC-Stained Slides of Follicular Lymphoma Using Iterative Watershed

Metin Nafi Gürcan, Siddharth Samsi, Gerard Lozanski, 2010, IEEE Transactions on Biomedical Engineering.

Automated global matching of temporal thoracic helical CT studies: feasibility study

Metin Nafi Gürcan, Russell C. Hardie, Steven K. Rogers, 2003, CARS.

Hotspot detection in pancreatic neuroendocrine tumors: density approximation by α-shape maps

M. Khalid Khan, Metin Nafi Gürcan, Liron Pantanowitz, 2016, SPIE Medical Imaging.

Efficient processing of pathological images using the grid: computer-aided prognosis of neuroblastoma

Jun Kong, Joel H. Saltz, Metin Nafi Gürcan, 2007, CLADE '07.

Cancer treatment outcome prediction by assessing temporal change: application to cervical cancer

Dongqing Zhang, Joel H. Saltz, Metin Nafi Gürcan, 2008, SPIE Medical Imaging.

Content-based image retrieval of centroblast cells and noncentroblast cells in Follicular lymphoma

Metin Nafi Gürcan, Hatice Çinar Akakin, Yagmur Gizem Cinar, 2012, 2012 20th Signal Processing and Communications Applications Conference (SIU).

Computer-Aided Grading of Neuroblastic Differentiation: Multi-Resolution and Multi-Classifier Approach

Kim L. Boyer, Jun Kong, Joel H. Saltz, 2007, 2007 IEEE International Conference on Image Processing.

Pathological image segmentation for neuroblastoma using the GPU

Kim L. Boyer, Jun Kong, Joel H. Saltz, 2008, 2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

Analysis and Semantic Querying in Large Biomedical Image Datasets

Jun Kong, Joel H. Saltz, Metin Nafi Gürcan, 2008, Computer.

A general framework for the segmentation of follicular lymphoma virtual slides

Metin Nafi Gürcan, Myriam Oger, Philippe Belhomme, 2012, Comput. Medical Imaging Graph..

Classification of glioblastoma and metastasis for neuropathology intraoperative diagnosis: a multi-resolution textural approach to model the background

Metin Nafi Gürcan, Mohammad Faizal Ahmad Fauzi, Hamza Numan Gokozan, 2014, Medical Imaging.

Hot spot detection for breast cancer in Ki-67 stained slides: image dependent filtering approach

M. Khalid Khan, Metin Nafi Gürcan, Erinn Downs-Kelly, 2014, Medical Imaging.

Applying knowledge-anchored hypothesis discovery methods to advance clinical and translational research: the OAMiner project

Metin Nafi Gürcan, Stephen L. James, Philip R. O. Payne, 2012, J. Am. Medical Informatics Assoc..

Tensor-based computation and modeling in multi-resolution digital pathology imaging: application to follicular lymphoma grading

Metin Nafi Gürcan, Gerard Lozanski, Evrim Acar, 2013, Medical Imaging.

Anatomically Anchored Template-Based Level Set Segmentation: Application to Quadriceps Muscles in MR Images from the Osteoarthritis Initiative

Metin Nafi Gürcan, Thomas M. Best, Jeffrey W. Prescott, 2011, Journal of Digital Imaging.

Identification of difficult to intubate patients from frontal face images using an ensemble of deep learning models

Metin Nafi Gürcan, Thomas E. Tavolara, Scott Segal, 2021, Comput. Biol. Medicine.