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Disentangled Autoencoder for Cross-Stain Feature Extraction in Pathology Image Analysis

Helge Hecht, Mhd Hasan Sarhan, Vlad Popovici
2020 Applied Sciences  
Finally, we demonstrate the utility of the proposed representation in the context of matching image patches for registration applications and for learning a bag of visual words for whole slide image summarization  ...  A novel deep autoencoder architecture is proposed for the analysis of histopathology images.  ...  Acknowledgments: We acknowledge the support of the RECETOX research infrastructure through the grant LM2018121 of the Czech Ministry of Education, Youth and Sports as well as of the CETOCOEN EXCELLENCE  ... 
doi:10.3390/app10186427 fatcat:bhrrj54hjfftjncmyb24de2pri

Front Matter: Volume 10140

Proceedings of SPIE, Metin N. Gurcan, John E. Tomaszewski
2017 Medical Imaging 2017: Digital Pathology  
.  The last two digits indicate publication order within the volume using a Base 36 numbering system employing both numerals and letters. These two-number sets start with 00, 01, 02, 03, 04,  ...  Publication of record for individual papers is online in the SPIE Digital Library. Paper Numbering: Proceedings of SPIE follow an e-First publication model.  ...  carcinoma-associated fibroblasts [10140-6] 10140 08 Lumen-based detection of prostate cancer via convolutional neural networks [10140-7] 10140 09 Hierarchical patch-based co-registration of differently  ... 
doi:10.1117/12.2270372 dblp:conf/midp/X17 fatcat:6yeb63ix6bau7jhipthayjih24

Towards More Reliable Unsupervised Tissue Segmentation Via Integrating Mass Spectrometry Imaging and Hematoxylin-Erosin Stained Histopathological Image [article]

Ang Guo, Zhiyu Chen, Fang Li, Wenbo Li, Qian Luo
2020 bioRxiv   pre-print
A spectrum of informative morphological features is computed iteratively for each patch and spatial segmentation can be generated by clustering the patches based on their morphological similarities.  ...  Specifically, besides molecular information from MSI data, we also obtain morphological information over a tissue section from its Hematoxylin-Erosin (H&E) stained histopathological image.  ...  and morphological information with HE staining histo-pathological image. The whole slide HE image is split into an array of small patches and each corresponds to a pixel of the MSI data.  ... 
doi:10.1101/2020.07.17.208025 fatcat:52owyestfffl3nhpfgctd762ne

What Can Machine Vision Do for Lymphatic Histopathology Image Analysis: A Comprehensive Review [article]

Xiaoqi Li, Haoyuan Chen, Chen Li, Md Mamunur Rahaman, Xintong Li, Jian Wu, Xiaoyan Li, Hongzan Sun, Marcin Grzegorzek
2022 arXiv   pre-print
This paper reviews the applications of image processing technology based on MV in lymphoma histopathological images in recent years, including segmentation, classification and detection.  ...  In particular, the continuous improvement of deep learning algorithms has further improved the accuracy of MV in disease detection and diagnosis.  ...  Acknowledgements This work is supported by the "National Natural Science Foundation of China" (No. 61806047), "Sichuan Science and Technology Program" (No. 2021YFH0069, 2021YFQ0057, 1614 2022YFS0565).  ... 
arXiv:2201.08550v2 fatcat:tzc4oiurzngkrlke4w4zt4f26u

High-throughput 3D whole-brain quantitative histopathology in rodents

Michel E. Vandenberghe, Anne-Sophie Hérard, Nicolas Souedet, Elmahdi Sadouni, Mathieu D. Santin, Dominique Briet, Denis Carré, Jocelyne Schulz, Philippe Hantraye, Pierre-Etienne Chabrier, Thomas Rooney, Thomas Debeir (+4 others)
2016 Scientific Reports  
With the rising use of automated slide staining systems and whole slide imaging microscopes, the capabilities for production of histopathological material as well as image digitization have dramatically  ...  Indeed, current standards for the analysis of brain histopathological markers heavily rely on manual intervention to delineate regions of interest (ROIs) and quantify the staining.  ...  To perform reproducible staining across the whole study, we used the Ventana Discovery XT slide staining system (Ventana Medical Systems, Inc.).  ... 
doi:10.1038/srep20958 pmid:26876372 pmcid:PMC4753455 fatcat:5wkcdpvcvffg7bqi5y3p2ugzru

Objective Diagnosis for Histopathological Images Based on Machine Learning Techniques: Classical Approaches and New Trends

Naira Elazab, Hassan Soliman, Shaker El-Sappagh, S. M. Riazul Islam, Mohammed Elmogy
2020 Mathematics  
They provide a detailed view of different types of diseases and their tissue status.  ...  Histopathology images are captured by a microscope to locate, examine, and classify many diseases, such as different cancer types.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/math8111863 fatcat:v22zj5qvbjem5dxrucs3q7dspu

Abstracts from USCAP 2020: Informatics (1522-1590)

2020 Laboratory Investigation  
Fat-rich and faintly-stained tissues are known to pose potential problems for whole slide scanning.  ...  The most common encountered artifacts were: acellular debris/mucin (29%), dark stained lymphocytes (23%) stain artifact/precipitate (23%).  ...  Conclusions: We demonstrate the feasibility of applying a DIA workflow for estimating stromal CD8+ TILs in NSCLC.  ... 
doi:10.1038/s41374-020-0393-8 pmid:32139865 fatcat:wecibsafmzhzjjgxqvxalr3xn4

Breast Cancer Multi-classification from Histopathological Images with Structured Deep Learning Model

Zhongyi Han, Benzheng Wei, Yuanjie Zheng, Yilong Yin, Kejian Li, Shuo Li
2017 Scientific Reports  
of binary classes (benign and malignant), and (2) the subtle differences in multiple classes due to the broad variability of high-resolution image appearances, high coherency of cancerous cells, and extensive  ...  Therefore, automated breast cancer multiclassification from histopathological images is of great clinical significance yet has never been explored.  ...  These are fine-grained high-resolution images from breast tissue biopsy slides stained with hematoxylin and eosin (H&E).  ... 
doi:10.1038/s41598-017-04075-z pmid:28646155 pmcid:PMC5482871 fatcat:gqwm7il56nc3rf6iintu4n4z74

GANs for Medical Image Analysis [article]

Salome Kazeminia, Christoph Baur, Arjan Kuijper, Bram van Ginneken, Nassir Navab, Shadi Albarqouni, Anirban Mukhopadhyay
2019 arXiv   pre-print
Furthermore, their ability to synthesize images at unprecedented levels of realism also gives hope that the chronic scarcity of labeled data in the medical field can be resolved with the help of these  ...  In this review paper, a broad overview of recent literature on GANs for medical applications is given, the shortcomings and opportunities of the proposed methods are thoroughly discussed and potential  ...  For example, in the case of synthesizing CT data, enveloping GANs synthesis with a physics-based simulation might ensure realistic HU values.  ... 
arXiv:1809.06222v3 fatcat:gfsmlq3uhvd4xeisaqagythgeq

Front Matter: Volume 9784

2016 Medical Imaging 2016: Image Processing  
4 SEGMENTATION: BRAIN 9784 0G Segmentation and labeling of the ventricular system in normal pressure hydrocephalus using patch-based tissue classification and multi-atlas labeling [9784-15] 9784 0H Generation  ...  estimation [9784-13] 9784 0F Automated segmentation of upper digestive tract from abdominal contrast-enhanced CT data using hierarchical statistical modeling of organ interrelations [9784-14] SESSION  ...  fluorescence imaging of decalcified teeth SESSION 8 MACHINE LEARNING 10 Slide-specific models for segmentation of differently stained digital histopathology whole slide images 9784 11 Relative value  ... 
doi:10.1117/12.2240619 fatcat:kot6cogf4rf6dcjhkzdrr5gahi

Scalable analysis of Big pathology image data cohorts using efficient methods and high-performance computing strategies

Tahsin Kurc, Xin Qi, Daihou Wang, Fusheng Wang, George Teodoro, Lee Cooper, Michael Nalisnik, Lin Yang, Joel Saltz, David J. Foran
2015 BMC Bioinformatics  
The content based image retrieval (CBIR) algorithms can quickly detect and retrieve image patches similar to a query patch using a hierarchical analysis approach.  ...  Results: The proposed tools and methods take advantage of state-of-the-art parallel machines and efficient content-based image searching strategies.  ...  Contract OCI-0910735, and the Nautilus system at the University of Tennessee's Center for Remote Data Analysis and Visualization supported by NSF Award ARRA-NSF-OCI-0906324.  ... 
doi:10.1186/s12859-015-0831-6 pmid:26627175 pmcid:PMC4667532 fatcat:lnnhszkk4vhi7d3yoi74t37e2m

A Survey of Methods for 3D Histology Reconstruction

Jonas Pichat, Juan Eugenio Iglesias, Tarek Yousry, Sébastien Ourselin, Marc Modat
2018 Medical Image Analysis  
This paper reviews almost three decades of methods for 3D reconstruction from serial sections, used in the study of many different types of tissue.  ...  of spatial correspondences; image registration is one technique that permits the automation of such a process and we describe recontruction methods that rely on it.  ...  Smriti Patodia, from UCL Institute of Neurology (Department of Neuropathology), for her comments on Section 2 and the images used in Figures  ... 
doi:10.1016/ pmid:29502034 fatcat:ta5hlvqjpzenxhltfwh6p4mhqq

Multispectral band selection and spatial characterization: Application to mitosis detection in breast cancer histopathology

H. Irshad, A. Gouaillard, L. Roux, D. Racoceanu
2014 Computerized Medical Imaging and Graphics  
images to improve the quality of the diagnostic in histopathology.  ...  This study aims at evaluating the accuracy of mitosis detection on histopathological multispectral images.  ...  Figure 4 :Figure 5 : 45 Example of different components of breast tissue in H&E stained histopathological image.  ... 
doi:10.1016/j.compmedimag.2014.04.003 pmid:24831181 fatcat:7cp7aqkamffclgsfmkuqkawjgq

Identifying in vivo DCE MRI markers associated with microvessel architecture and gleason grades of prostate cancer

Asha Singanamalli, Mirabela Rusu, Rachel E. Sparks, Natalie N.C. Shih, Amy Ziober, Li-Ping Wang, John Tomaszewski, Mark Rosen, Michael Feldman, Anant Madabhushi
2015 Journal of Magnetic Resonance Imaging  
Representative slices from RP specimens were stained with vascular marker CD31.  ...  Tumor extent was mapped from RP sections onto DCE MRI using nonlinear registration methods. 77 microvessel QH features and 18 DCE MRI kinetic features were extracted and evaluated for their ability to  ...  extraction and image co-registration methods.  ... 
doi:10.1002/jmri.24975 pmid:26110513 pmcid:PMC4691230 fatcat:uu6nw5uh7jf2vcuki33g2fg2we

An Image Analysis Resource for Cancer Research: PIIP—Pathology Image Informatics Platform for Visualization, Analysis, and Management

Anne L. Martel, Dan Hosseinzadeh, Caglar Senaras, Yu Zhou, Azadeh Yazdanpanah, Rushin Shojaii, Emily S. Patterson, Anant Madabhushi, Metin N. Gurcan
2017 Cancer Research  
Thus far, new plugins have been developed and incorporated into the platform for out of focus detection, region of interest transforma-tion, and IHC slide analysis.  ...  The goal of this project is to develop and embed some commonly used image analysis applications into the Sedeen viewer to create a freely available resource for the digital pathology and cancer research  ...  Acknowledgments We are grateful to Craig Madho and Deyu Wang at Pathcore for their help in the coordination of the project and facilitating the writing process.  ... 
doi:10.1158/0008-5472.can-17-0323 pmid:29092947 fatcat:pthivt4fbja4vakr6wkno5sary
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