Humayun Irshad
Cited by
Cited by
Diagnostic assessment of deep learning algorithms for detection of lymph node metastases in women with breast cancer
BE Bejnordi, M Veta, PJ Van Diest, B Van Ginneken, N Karssemeijer, ...
Jama 318 (22), 2199-2210, 2017
Deep learning for identifying metastatic breast cancer
D Wang, A Khosla, R Gargeya, H Irshad, AH Beck
arXiv preprint arXiv:1606.05718, 2016
Methods for Nuclei Detection, Segmentation and Classification in Digital Histopathology: A Review. Current Status and Future Potential
H Irshad, A Veillard, L Roux, D Racoceanu
IEEE Review on BioMedical Engineering 7 (1), 97--114, 2014
Mitosis Detection in Breast Cancer Histological Images
L Roux, D Racoceanu, N Loménie, M Kulikova, H Irshad, J Klossa, ...
Journal of Pathology Informatics 4 (1), 8, 2013
Image segmentation using fuzzy clustering: A survey
S Naz, H Majeed, H Irshad
2010 6th international conference on emerging technologies (ICET), 181-186, 2010
Nanoscale imaging of clinical specimens using pathology-optimized expansion microscopy
Y Zhao, O Bucur, H Irshad, F Chen, A Weins, AL Stancu, EY Oh, ...
Nature biotechnology 35 (8), 757-764, 2017
Automated Mitosis Detection in Histopathology using Morphological and Multi-Channel Statistics Features
H Irshad
Journal of Pathology Informatics 5 (13), 6, 2013
Crowdsourcing image annotation for nucleus detection and segmentation in computational pathology: evaluating experts, automated methods, and the crowd
H Irshad, L Montaser-Kouhsari, G Waltz, O Bucur, JA Nowak, F Dong, ...
Pacific symposium on biocomputing Co-chairs, 294-305, 2014
Computational pathology to discriminate benign from malignant intraductal proliferations of the breast
F Dong, H Irshad, EY Oh, MF Lerwill, EF Brachtel, NC Jones, ...
PloS one 9 (12), e114885, 2014
Automated Mitosis Detection Using Texture, SIFT Features and HMAX Biologically Inspired Approach
H Irshad, S Jalali, L Roux, D Racoceanu, LJ Hwee, G Le Naour, F Capron
Journal of Pathology Informatics 4 (12), 7, 2013
Deep learning for identifying metastatic breast cancer. arXiv 2016
D Wang, A Khosla, R Gargeya, H Irshad, AH Beck, B Israel
arXiv preprint arXiv:1606.05718, 0
Multispectral Band Selection and Spatial Characterization: Application to Mitosis Detection in Breast Cancer Histopathology
H Irshad, A Gouaillard, L Roux, D Racoceanu
Computerized Medical Imaging and Graphics (CMIG) 38 (5), 390--402, 2014
Automated Clear Cell Renal Carcinoma Grade Classification with Prognostic Significance
K Tian, CA Rubadue, DI Lin, M Veta, ME Pyle, H Irshad, YJ Heng
PLoS One 14 ((10)), 661520, 2019
Crowdsourcing scoring of immunohistochemistry images: Evaluating Performance of the Crowd and an Automated Computational Method
H Irshad, EY Oh, D Schmolze, M Quintana, Liza, L Collins, RM Tamimi, ...
Scientific Reports 7, 43286, 2017
Multi-channels statistical and morphological features based mitosis detection in breast cancer histopathology
H Irshad, L Roux, D Racoceanu
2013 35th Annual International Conference of the IEEE Engineering in …, 2013
Image fusion using computational intelligence: A survey
H Irshad, M Kamran, AB Siddiqui, A Hussain
2009 Second International Conference on Environmental and Computer Science …, 2009
Assisted image annotation
H Irshad, SQ Mirsharif, K Vajapey, C Monchu, C Xiao, R Munro
US Patent 11,176,415, 2021
Spectral Band Selection For Mitosis Detection in Histopathology
H Irshad, A Gouaillard, L Roux, D Racoceanu
11th IEEE International Symposium on Biomedical Imaging (ISBI), 2014
Video object tracking
K Vajapey, R Munro, JR Cloughley, MA Gordon, H Irshad, C Monchu, ...
US Patent 10,489,918, 2019
Diagnostic assessment of deep learning algorithms for detection and segmentation of lesion in mammographic images
T Boot, H Irshad
Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020
The system can't perform the operation now. Try again later.
Articles 1–20