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Publications

2020

  • A. Pennycuick, V. H Teixeira, K. AbdulJabbar, S. E. A. Raza, T. Lund, A. U. Akarca, R. Rosenthal, L. Kalinke, D. P. Chandrasekharan, C. P. Pipinikas, H. Lee-Six, R. E. Hynds, K. H.C. Gowers, J. Y Henry, F. R. Millar, Y. B Hagos, C. Denais, M. Falzon, D. A Moore, S. Antoniou, P. F. Durrenberger, A. J. S. Furness, B. Carroll, C. Marceaux, M.e Asselin-Labat, W. Larson, C. Betts, L. M. Coussens, R. M. Thakrar, J. George, C. Swanton, C. Thirlwell, P. J. Campbell, T. Marafioti, Y. Yuan, S. A. Quezada, N. McGranahan, S. M. Janes, “Immune surveillance in clinical regression of pre-invasive squamous cell lung cancer,” Cancer Discovery, July 2020. [Abstract] [doi]
  • K. AbdulJabbar*, S. E. A. Raza*, R. Rosenthal, M. Jamal-Hanjani, S. Veeriah, A. Akarca, T. Lund, D. Moore, R. Salgado, M. Al Bakir, L. Zapata, C. Hiley, L. Officer, M. Sereno, C. Smith, S. Loi, A. Hackshaw, T. Marafioti, S. Quezada, N. McGranahan, J. Le Quesne, C. Swanton & Y. Yuan, “Geospatial immune variability illuminates differential evolution of lung adenocarcinoma,” Nature Medicine, May 2020, p. 1-9. [Abstract] [doi]
  • R. M. S. Bashir, H. Mahmood, M. Shaban, S. E. A. Raza, M. M. Fraz, S. A. Khurram & N. M. Rajpoot, “Automated grade classification of oral epithelial dysplasia using morphometric analysis of histology images,” in Medical Imaging 2020: Digital Pathology, Houston, Texas, USA, vol. 11320, p. 1132011. [Abstract] [doi]

2019

  • S. Graham, Q. Dang, S. E. A. Raza, J.T. Kwak, N.M. Rajpoot, “Hover-Net: Simultaneous segmentation and classification of nuclei in multi-tissue histology images,” Medical Image Analysis, Dec. 2019, vol. 58, p. 101563. [Abstract] [doi] [Data]
  • K. Zormpas-Petridis, H. Failmezger, S. E. A. Raza, et al., “Superpixel-based Conditional Random Fields (SuperCRF): Incorporating global and local context for enhanced deep learning in melanoma histopathology,” Frontiers in Oncology, Sep. 2019. [Abstract] [doi]
  • S. E. A. Raza, K. AbdulJabbar, M. Jamal-Hanjani, et al., “Deconvolving convolution neural network for cell detection,” IEEE International Symposium on Biomedical Imaging (ISBI), Apr. 2019, p. 891–894. [Abstract] [doi]

2018

  • S. E. A. Raza, L. Cheung, M. Shaban, et al., “Micro-Net: A unified model for segmentation of various objects in microscopy images,” Medical Image Analysis, Dec. 2018, vol. 52, p. 160–173. [Abstract] [doi] [Data]
  • P. L. Narayanan, S. E. A. Raza, A. Dodson, et al., “DeepSDCS: Dissecting cancer proliferation heterogeneity in Ki67 digital whole slide images,” in Medical Imaging with Deep Learning (MIDL) , 2018 [Abstract] [doi]
  • N. Alsubaie, K. Sirinukunwattana, S. E. A. Raza, et al., “A bottom-up approach for tumour differentiation in whole slide images of lung adenocarcinoma,” in Medical Imaging : Digital Pathology, Mar. 2018, pp. 105810E, vol. 10581. [Abstract] [doi]

2017

  • S. E. A. Raza, L. Cheung, D. Epstein, et al., “Mimonet: Gland segmentation using multi-input-multi-output convolutional neural network,” In Medical Image Understanding and Analysis (MIUA), Jul. 2017, pp. 698–706. [Abstract] [doi]
  • S. E. A. Raza, L. Cheung, D. Epstein, et al., “MIMO-Net: A multi-input multi-output convolutional neural network for cell segmentation in fluorescence microscopy images,” IEEE International Symposium on Biomedical Imaging (ISBI), Apr. 2017, p. 337-340. [Abstract] [doi]
  • G. Li, S.E.A. Raza, N.M. Rajpoot, “Multi-Resolution Cell Orientation Congruence Descriptors for Epithelium Segmentation in Endometrial Histology Images,” Medical Image Analysis, Jan. 2017, vol. 37, p. 91–100. [Abstract] [doi]
  • N. Alsubaie, N. Trahearn, S.E.A. Raza et al., “Stain Deconvolution Using Statistical Analysis of Multi-Resolution Stain Colour Representation,” PLoS One, Jan. 2017, vol. 12, no. 1, p.e0169875. [Abstract] [doi]

2016

  • N. Alsubaie, S. E. A. Raza, and N. M. Rajpoot, “Stain Deconvoloution of Histology Images via Independent Component Analysis in the Wavelet Domain,” IEEE International Symposium on Biomedical Imaging (ISBI), Apr. 2016, p. 803-806. [Abstract] [doi]
  • M.N. Kashif, S.E.A. Raza, K. Sirinukunwattana, et al., “Handcrafted features with convolutional neural networks for detection of tumor cells in histology images,” IEEE International Symposium on Biomedical Imaging (ISBI), Apr. 2016, p. 1029-1032. [Abstract] [doi]
  • S. E. A. Raza, D. Langenkämper, K. Sirinukunwattana, D. B. A. Epstein, T. W. Nattkemper, and N. M. Rajpoot, “Robust Normalization Protocols for Multiplexed Fluorescence Bioimage Analysis,” BMC Biodata Min., Mar. 2016, vol. 9:11. [Abstract] [doi]
  • K. Sirinukunwattana, S.E.A. Raza, Y.-W. Tsang, D. Snead, I. Cree, and N.M. Rajpoot, “Locality Sensitive Deep Learning for Detection and Classification of Nuclei in Routine Colon Cancer Histology Images,” IEEE Trans. Med. Imaging, pp. 1–1, Jan. 2016. [Abstract] [doi] [Data]

2015

  • K. Sirinukunwattana, S. E. A.Raza, Y.-W. Tsang, D. Snead, I. Cree, and N.M. Rajpoot, “A Spatially Constrained Deep Learning Framework for Detection of Epithelial Tumor Nuclei in Cancer Histology Images,” in 1st International Workshop on Patch-based Techniques in Medical Imaging, MICCAI, Oct. 2015, pp. 154–162. [Abstract] [doi]
  • G. Li, S. E. A. Raza, and N.M. Rajpoot, “A Novel Cell Orientation Congruence Descriptor for Superpixel Based Epithelium Segmentation in Endometrial Histology Images,” in 1st International Workshop on Patch-based Techniques in Medical Imaging, MICCAI, Oct. 2015, pp. 172–179. [Abstract] [doi]
  • S.E.A. Raza, V. Sanchez, G. Prince, J. Clarkson, and N. M. Rajpoot, “Registration of thermal and visible light images of diseased plants using silhouette extraction in the wavelet domain,” Pattern Recognit., vol. 48, pp. 2119–2128, Jul. 2015. [Abstract] [doi][Software]
  • S. E. A. Raza and N. M. Rajpoot, “Cell Nuclei Segmentation in Variable Intensity Fluorescence Microscopy Images,” in Medical Image Understanding and Analysis, Jul. 2015, pp. 28–33. [Abstract] [doi]
  • N. Alsubaie, N. Trahearn, S. E. A. Raza, and N. M. Rajpoot, “A Discriminative Framework for Stain Deconvolution of Histopathology Images in the Maxwellian Space,” in Medical Image Understanding and Analysis, Jul. 2015, pp. 132–137. [Abstract] [doi]
  • S. E. A. Raza, G. Prince, J. Clarkson, and N. M. Rajpoot, “Automatic Detection of Diseased Tomato Plants using Thermal and Stereo Visible Light Images,” PLoS One, Apr. 2015. [Abstract] [doi]
  • S. E. A. Raza, M. Q. Marjan, M. Arif, F. Butt, F. Sultan, and N. M. Rajpoot, “Anisotropic tubular filtering for automatic detection of acid-fast bacilli in Ziehl-Neelsen stained sputum smear samples,” in SPIE Medical Imaging, Feb. 2015, vol. 9420, p. 942005. [Abstract] [doi]

2014

  • A.M. Khan, S.E.A. Raza, M. Khan, et al., “Cell Phenotyping in Multi-Tag Fluorescent Bioimages,” Neurocomputing, Jun. 2014, vol. 134 no. 1 p. 254-261. [Abstract] [doi]
  • S.E.A Raza, H. Smith, G.J.J. Clarkson, et al., “Automatic Detection of Regions in Spinach Canopies Responding to Soil Moisture Deficit Using Combined Visible and Thermal Imagery,” PLoS ONE, Jun. 2014, vol. 9 no. 6 p. e97612. [Abstract] [doi]

2012

  • S.E.A. Raza, A. Humayun, S. Abouna, et al., “RAMTaB: Robust Alignment of Multi-Tag Bioimages,” PLoS ONE, Feb. 2012, vol. 7 no. 2, p. e30894. [Abstract] [doi][Software]
  • A. M. Khan, A. Humayun, S. E. A. Raza, et al., “A Novel Paradigm for Mining Cell Phenotypes in Multi-tag Bioimages Using a Locality Preserving Nonlinear Embedding,” Proceedings Neural Information Processing. ICONIP, Lecture Notes in Computer Science , vol. 7666, 2012. [Abstract] [doi]

2011

  • A. Humayun, S.E.A. Raza, C. Waddington, et al., “A Framework for Molecular Co-Expression Pattern Analysis in Multi-Channel Toponome Fluorescence Images,” Proceedings Microscopy Image Analysis with Applications in Biology (MIAAB), Sep. 2011, Heidelberg, Germany. [Abstract] [doi]