M Khalid Khan Niazi

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Metin N. GurcanDirector, Center for Artificial Intelligence Research, Wake Forest University School of MedicineCorreu electrònic verificat a wakehealth.edu
Thomas Erol TavolaraMayo ClinicCorreu electrònic verificat a mayo.edu
Anil ParwaniProfessor of Pathology and Biomedical InformaticsCorreu electrònic verificat a osumc.edu
Gillian BeamerTufts UniversityCorreu electrònic verificat a tufts.edu
Ziyu SuThe Ohio State University Wexner Medical CenterCorreu electrònic verificat a osumc.edu
Çağlar ŞenarasPlanet LabsCorreu electrònic verificat a planet.com
Bülent YenerProfessor of Computer Science, Director of Data Science Research Center RPICorreu electrònic verificat a cs.rpi.edu
Sang Jin LeeProfessor of Wake Forest Institute for Regenerative MedicineCorreu electrònic verificat a wakehealth.edu
Muhammad Aurangzeb KhanWellcome Trust Centre Cell-Matrix Research, Faculty of Biology, Medicine and Health, University ofCorreu electrònic verificat a manchester.ac.uk
Mostafa RezapourWake Forest Institute for Regenerative Medicine (WFIRM), Wake Forest University School of MedicineCorreu electrònic verificat a wakehealth.edu
Wei ChenThe Ohio State UniversityCorreu electrònic verificat a osumc.edu
Liron PantanowitzPathologist, University of PittsburghCorreu electrònic verificat a pitt.edu
Berkman SahinerUS Food and Drug Administration and ARPA-HCorreu electrònic verificat a fda.hhs.gov
Meryem Uzun-PerR&D Manager at BiletBank & Assist. Prof. at ISTUNCorreu electrònic verificat a petour.com
Usama SajjadThe Ohio State UniversityCorreu electrònic verificat a osumc.edu
Arwa Shana'ahCorreu electrònic verificat a osumc.edu
Nimit DhulekarThe MathWorksCorreu electrònic verificat a mathworks.com
Ewert Bengtssonprofessor emeritus in digital image analysis at Uppsala UniversityCorreu electrònic verificat a cb.uu.se
Ingela NyströmProfessor in Visualization, Centre for Image Analysis, Dept. of Information Technology, Uppsala UnivCorreu electrònic verificat a it.uu.se
Seda ÇamalanMayo ClinicCorreu electrònic verificat a mayo.edu

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M Khalid Khan Niazi

The Ohio State University

Correu electrònic verificat a osumc.edu - Pàgina d'inici

Quantitative Microscopy Digital Pathology Computational Pathology Quantitative Image Analysis


Títol Ordena per cites Ordena per any Ordena per títol	Citada per Citada per	Any
Digital pathology and artificial intelligence MKK Niazi, AV Parwani, MN Gurcan The Lancet Oncology 20 (5), e253-e261, 2019	1068	2019
DeepFocus: Detection of out-of-focus regions in whole slide digital images using deep learning C Senaras, MKK Niazi, G Lozanski, M Nafi Gurcan PLOS ONE, 2018	128	2018
Lung necrosis and neutrophils reflect common pathways of susceptibility to Mycobacterium tuberculosis in genetically diverse, immune competent mice. MKK Niazi, N Dhulekar, D Schmidt, S Major, R Cooper, C Abeijon, D Gatti, ... Disease Models & Mechanisms, 2015	126	2015
Velocity and pressure-based partitions of horizontal and vertical trajectories for on-line signature verification MT Ibrahim, MA Khan, KS Alimgeer, MK Khan, IA Taj, L Guan Pattern Recognition 43 (8), 2817-2832, 2010	67	2010
Optimized generation of high-resolution phantom images using cGAN: Application to quantification of Ki67 breast cancer images C Senaras, MKK Niazi, B Sahiner, MP Pennell, G Tozbikian, G Lozanski, ... PLOS ONE 13 (5), e0196846, 2018	65	2018
Identifying tumor in pancreatic neuroendocrine neoplasms from Ki67 images using transfer learning MKK Niazi, T Tavolara, V Arole, D Hartman, L Pantanowitz, MN Gurcan PLOS ONE, 2018	59	2018
Coronary angiogram image enhancement using decimation-free directional filter banks MAU Khan, MK Khan, MA Khan Acoustics, Speech, and Signal Processing, 2004. Proceedings.(ICASSP'04 …, 2004	59	2004
The influence of printing parameters and cell density on bioink printing outcomes GJ Gillispie, A Han, M Uzun-Per, J Fisher, AG Mikos, MKK Niazi, JJ Yoo, ... Tissue Engineering Part A 26 (23-24), 1349-1358, 2020	58	2020
Ki-67 assessment of pancreatic neuroendocrine neoplasms: Systematic review and meta-analysis of manual vs. digital pathology scoring C Luchini, L Pantanowitz, V Adsay, SL Asa, P Antonini, I Girolami, ... Modern Pathology, 1-9, 2022	49	2022
OtoMatch: Content-based eardrum image retrieval using deep learning C Seda, MKK Niazi, AC Moberly, T Teknos, G G, Essig, C Elmaraghy, ... PLOS One 15 (5), e0232776, 2020	49	2020
Ros‐NET: A deep convolutional neural network for automatic identification of rosacea lesions H Binol, A Plotner, J Sopkovich, B Kaffenberger, MKK Niazi, MN Gurcan Wiley Skin Research &Technology (https://doi.org/10.1111/srt.12817), 2019	49	2019
Identification of difficult to intubate patients from frontal face images using an ensemble of deep learning models TE Tavolara, MN Gurcan, S Segal, MKK Niazi Computers in Biology and Medicine 136, 104737, 2021	46	2021
Attention2majority: Weak multiple instance learning for regenerative kidney grading on whole slide images Z Su, TE Tavolara, G Carreno-Galeano, SJ Lee, MN Gurcan, MKK Niazi Medical Image Analysis 79, 102462, 2022	44	2022
Visually Meaningful Histopathological Features for Automatic Grading of Prostate Cancer MKK Niazi, K Yao, D Zynger, S Clinton, J Chen, M Koyuturk, ... IEEE Journal of Biomedical and Health Informatics 2 (4), 1027 - 1038, 2017	44	2017
Velocity-image model for online signature verification MAU Khan, MKK Niazi, MA Khan Image Processing, IEEE Transactions on 15 (11), 3540-3549, 2006	43	2006
Deep learning predicts gene expression as an intermediate data modality to identify susceptibility patterns in Mycobacterium tuberculosis infected Diversity Outbred mice TE Tavolara, M Niazi, A Gower, M Ginese, B Gillian, MN Gurcan Lancet EBioMedicine 67 (2021), 1-12, 2021	34	2021
Genetically diverse mice are novel and valuable models of age-associated susceptibility to Mycobacterium tuberculosis DE Harrison, CM Astle, MKK Niazi, S Major, GL Beamer Immunity & Ageing, 2015	34	2015
Impact of Diffusion Barriers to Small Cytotoxic Molecules on the Efficacy of Immunotherapy in Breast Cancer VC Hiranmoy Das, Zhihui Wang, M Khalid Khan Niazi PLOS ONE, 2013	33	2013
On-line signature verification by exploiting inter-feature dependencies M Khalid Khan, M Aurangzeb Khan, MAU Khan, I Ahmad Pattern Recognition, 2006. ICPR 2006. 18th International Conference on 2 …, 2006	32	2006
CXCL1: A new diagnostic biomarker for human tuberculosis discovered using Diversity Outbred mice D Koyuncu, MKK Niazi, T Tavolara, C Abeijon, ML Ginese, Y Liao, C Mark, ... PLOS Pathogens 17 (8), e1009773, 2021	31	2021

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