World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
41
Citations
10252
World Ranking
6816
National Ranking
1854

Metin N. Gurcan publication distribution in Engineering and Technology in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Engineering and Technology in 2026. The highlighted bar marks where Metin N. Gurcan sits on this spectrum.

38–47 publications: 20 scientists 48–57 publications: 35 scientists 58–67 publications: 96 scientists 68–77 publications: 135 scientists 78–87 publications: 190 scientists 88–97 publications: 259 scientists 98–107 publications: 283 scientists 108–117 publications: 369 scientists 118–127 publications: 341 scientists 128–137 publications: 386 scientists 138–147 publications: 372 scientists 148–157 publications: 457 scientists 158–167 publications: 415 scientists 168–177 publications: 407 scientists 178–187 publications: 421 scientists 188–197 publications: 378 scientists 198–207 publications: 403 scientists 208–217 publications: 317 scientists 218–227 publications: 346 scientists 228–237 publications: 321 scientists 238–247 publications: 260 scientists 248–257 publications: 280 scientists 258–267 publications: 240 scientists 268–277 publications: 214 scientists 278–287 publications: 242 scientists 288–297 publications: 203 scientists 298–307 publications: 166 scientists 308–317 publications: 154 scientists 318–327 publications: 175 scientists 328–337 publications: 159 scientists 338–347 publications: 99 scientists 348–357 publications: 131 scientists 358–367 publications: 106 scientists 368–377 publications: 118 scientists 378–387 publications: 97 scientists 388–397 publications: 108 scientists 398–407 publications: 82 scientists 408–417 publications: 71 scientists 418–427 publications: 64 scientists 428–437 publications: 55 scientists 438–447 publications: 54 scientists 448–457 publications: 60 scientists 458–467 publications: 47 scientists 468–477 publications: 40 scientists 478–487 publications: 30 scientists 488–497 publications: 29 scientists 498–507 publications: 38 scientists 508–517 publications: 40 scientists 518–527 publications: 32 scientists 528–537 publications: 23 scientists 538–547 publications: 28 scientists 548–557 publications: 23 scientists 558–567 publications: 19 scientists 568–577 publications: 16 scientists 578–587 publications: 17 scientists 588–597 publications: 18 scientists 598–607 publications: 22 scientists 608–617 publications: 15 scientists 618–627 publications: 9 scientists 628–637 publications: 11 scientists 638–647 publications: 21 scientists 648–657 publications: 12 scientists 658–667 publications: 9 scientists 668–677 publications: 11 scientists 678–687 publications: 9 scientists 688–697 publications: 6 scientists 698–707 publications: 14 scientists 708–717 publications: 7 scientists 718–727 publications: 8 scientists 728–737 publications: 10 scientists 738–747 publications: 9 scientists 748–757 publications: 5 scientists 758–767 publications: 5 scientists 768–777 publications: 11 scientists 778–787 publications: 7 scientists 788–797 publications: 2 scientists 798–803 publications: 4 scientists 804+ publications: 100 scientists
38 publications 804+

This scientist: 225 publications — 57th percentile

57% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 804 publications or more.

Metin N. Gurcan D-index placement in Engineering and Technology in 2026

The chart shows the D-index (discipline H-index) distribution of Engineering and Technology scientists ranked by Research.com in 2026. The highlighted bar marks where Metin N. Gurcan sits on this spectrum.

30 D-Index: 59 scientists 31 D-Index: 114 scientists 32 D-Index: 129 scientists 33 D-Index: 189 scientists 34 D-Index: 200 scientists 35 D-Index: 262 scientists 36 D-Index: 311 scientists 37 D-Index: 312 scientists 38 D-Index: 350 scientists 39 D-Index: 385 scientists 40 D-Index: 348 scientists 41 D-Index: 362 scientists 42 D-Index: 426 scientists 43 D-Index: 380 scientists 44 D-Index: 310 scientists 45 D-Index: 341 scientists 46 D-Index: 301 scientists 47 D-Index: 306 scientists 48 D-Index: 271 scientists 49 D-Index: 246 scientists 50 D-Index: 210 scientists 51 D-Index: 253 scientists 52 D-Index: 213 scientists 53 D-Index: 221 scientists 54 D-Index: 195 scientists 55 D-Index: 186 scientists 56 D-Index: 170 scientists 57 D-Index: 167 scientists 58 D-Index: 166 scientists 59 D-Index: 144 scientists 60 D-Index: 152 scientists 61 D-Index: 141 scientists 62 D-Index: 138 scientists 63 D-Index: 131 scientists 64 D-Index: 118 scientists 65 D-Index: 114 scientists 66 D-Index: 119 scientists 67 D-Index: 95 scientists 68 D-Index: 87 scientists 69 D-Index: 77 scientists 70 D-Index: 89 scientists 71 D-Index: 69 scientists 72 D-Index: 54 scientists 73 D-Index: 46 scientists 74 D-Index: 55 scientists 75 D-Index: 54 scientists 76 D-Index: 49 scientists 77 D-Index: 53 scientists 78 D-Index: 46 scientists 79 D-Index: 28 scientists 80 D-Index: 39 scientists 81 D-Index: 36 scientists 82 D-Index: 24 scientists 83 D-Index: 26 scientists 84 D-Index: 36 scientists 85 D-Index: 18 scientists 86 D-Index: 25 scientists 87 D-Index: 19 scientists 88 D-Index: 26 scientists 89 D-Index: 27 scientists 90 D-Index: 23 scientists 91 D-Index: 15 scientists 92 D-Index: 12 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 13 scientists 97 D-Index: 13 scientists 98 D-Index: 9 scientists 99 D-Index: 7 scientists 100 D-Index: 7 scientists 101 D-Index: 8 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 9 scientists 105 D-Index: 6 scientists 106 D-Index: 9 scientists 107+ D-Index: 99 scientists
30 D-Index 107+

This scientist: 41 D-Index — 31st percentile

31% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 107 D-Index or more.

Research.com Recognitions

  • 2019 - SPIE Fellow

Overview

Metin N. Gurcan is affiliated with Wake Forest University in the United States and has contributed extensively to research in the field of Medicine, with a total of 143 publications. Their work spans several subfields, including Radiology, Nuclear Medicine and Imaging, Artificial Intelligence, Molecular Biology, Epidemiology, and Surgery.

The scientist has authored research addressing a range of topics such as AI in cancer detection, Radiomics and Machine Learning in Medical Imaging, Cell Image Analysis Techniques, Ear Surgery and Otitis Media, Reconstructive Facial Surgery Techniques, Tuberculosis Research and Epidemiology, and Digital Imaging for Blood Diseases.

Frequent co-authors collaborating with Metin N. Gurcan include Muhammad Khalid Khan Niazi, Mostafa Rezapour, Thomas E. Tavolara, Ziyu Su, and Aaron C. Moberly.

Metin N. Gurcan has published papers in various well-known venues. Some of the more frequent publication venues are bioRxiv (Cold Spring Harbor Laboratory), arXiv (Cornell University), Alzheimer's & Dementia, Cancers, and PLoS ONE.

Representative recent papers include:

  • Convolutional Neural Network-Based Clinical Predictors of Oral Dysplasia: Class Activation Map Analysis of Deep Learning Results, 2021, Cancers
  • Ki-67 assessment of pancreatic neuroendocrine neoplasms: Systematic review and meta-analysis of manual vs. digital pathology scoring, 2022, Modern Pathology
  • Cloud-Based Federated Learning Implementation Across Medical Centers, 2021, JCO Clinical Cancer Informatics
  • Bioreactor design and validation for manufacturing strategies in tissue engineering, 2021, Bio-Design and Manufacturing
  • Identification of difficult to intubate patients from frontal face images using an ensemble of deep learning models, 2021, Computers in Biology and Medicine

In addition to articles, Metin N. Gurcan has published a book titled Brain Tumor Segmentation, Grading and Patient Survival Prediction in 2023 through Frontiers Media.

The scientist was recognized as an SPIE Fellow in 2019.

Best Publications

  • Histopathological Image Analysis: A Review

    M.N. Gurcan;L.E. Boucheron;A. Can;A. Madabhushi

  • Digital pathology and artificial intelligence

    Muhammad Khalid Khan Niazi;Anil V Parwani;Metin N Gurcan

  • Diagnosis of thyroid cancer using deep convolutional neural network models applied to sonographic images: a retrospective, multicohort, diagnostic study.

    Xiangchun Li;Sheng Zhang;Qiang Zhang;Xi Wei

  • Lung nodule detection on thoracic computed tomography images: Preliminary evaluation of a computer-aided diagnosis system

    Metin N. Gurcan;Berkman Sahiner;Nicholas Petrick;Heang Ping Chan

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

    O. Sertel;J. Kong;H. Shimada;U. V. Catalyurek

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

    Hui Kong;M. Gurcan;K. Belkacem-Boussaid

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

    B. Sahiner;N. Petrick;Heang-Ping Chan;L.M. Hadjiiski

  • Computerized classification of intraductal breast lesions using histopathological images

    M M Dundar;S Badve;G Bilgin;V Raykar

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

    Olcay Sertel;Jun Kong;Umit V. Catalyurek;Gerard Lozanski

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

    J. Kong;O. Sertel;H. Shimada;K. L. Boyer

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

    H. C. Akakin;M. N. Gurcan

  • Image analysis for neuroblastoma classification: segmentation of cell nuclei.

    Metin N. Gurcan;Tony Pan;Hiroyuki Shimada;Joel H. Saltz

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

    G. Teodoro;R. Sachetto;O. Sertel;M.N. Gurcan

  • Detection of microcalcifications in mammograms using higher order statistics

    M.N. Gurcan;Y. Yardimci;A.E. Cetin;R. Ansari

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

    O Sertel;G Lozanski;M N Gurcan

  • Convolutional Neural Network-Based Clinical Predictors of Oral Dysplasia: Class Activation Map Analysis of Deep Learning Results.

    Seda Camalan;Hanya Mahmood;Hamidullah Binol;Anna Luiza Damaceno Araújo

  • Analysis of temporal changes of mammographic features: computer-aided classification of malignant and benign breast masses.

    Lubomir Hadjiiski;Berkman Sahiner;Heang-Ping Chan;Nicholas Petrick

  • Semi-automated segmentation to assess the lateral meniscus in normal and osteoarthritic knees.

    M.S. Swanson;J.W. Prescott;T.M. Best;K. Powell

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

    Lee Cooper;Olcay Sertel;Jun Kong;Gerard Lozanski

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

    Hammad Qureshi;Olcay Sertel;Nasir Rajpoot;Roland Wilson

  • Optimal neural network architecture selection: improvement in computerized detection of microcalcifications.

    Metin N. Gurcan;Heang Ping Chan;Berkman Sahiner;Lubomir Hadjiiski

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

    Sufyan Y. Ababneh;Jeffrey W. Prescott;Metin N. Gurcan

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

    O. Sertel;Jun Kong;G. Lozanski;A. Shana'ah

  • Vessel segmentation from abdominal magnetic resonance images: adaptive and reconstructive approach.

    Evgin Goceri;Zarine K. Shah;Metin N. Gurcan

  • Optimized generation of high-resolution phantom images using cGAN: Application to quantification of Ki67 breast cancer images

    Caglar Senaras;Muhammad Khalid Khan Niazi;Berkman Sahiner;Michael P. Pennell

  • Computerized microscopic image analysis of follicular lymphoma

    Olcay Sertel;Jun Kong;Gerard Lozanski;Ümit V. Çatalyürek

Frequent Co-Authors

Joel H. Saltz
Joel H. Saltz Stony Brook University
Ümit V. Çatalyürek
Ümit V. Çatalyürek Georgia Institute of Technology
Berkman Sahiner
Berkman Sahiner United States Food and Drug Administration
Heang Ping Chan
Heang Ping Chan University of Michigan–Ann Arbor
Lubomir M. Hadjiiski
Lubomir M. Hadjiiski University of Michigan–Ann Arbor
Anant Madabhushi
Anant Madabhushi Emory University
Nicholas Petrick
Nicholas Petrick US Food and Drug Administration
Hiroyuki Shimada
Hiroyuki Shimada Stanford University
Rebecca D. Jackson
Rebecca D. Jackson The Ohio State University
Thomas M. Best
Thomas M. Best University of Miami

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