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A Two-Phase Mitosis Detection Approach Based on U-Shaped Network

Wenjing Lu, Qiushi Zhao
2021 BioMed Research International  
This paper proposes a deep learning-based method for mitosis detection in breast histopathology images.  ...  Based on the generated bounding boxes, an object detection network is trained to accomplish mitosis detection.  ...  Generally, breast cancer can be classified into three levels in histopathology based on the morphological microstructure of cancerous and the normal cells, i.e., well differentiated, poorly differentiated  ... 
doi:10.1155/2021/1722652 pmid:34651044 pmcid:PMC8510810 fatcat:us5cit26qna5hldu5vbqf7u64a

Deep learning in mammography and breast histology, an overview and future trends

Azam Hamidinekoo, Erika Denton, Andrik Rampun, Kate Honnor, Reyer Zwiggelaar
2018 Medical Image Analysis  
CAD systems developed for mammography and breast histopathology images is presented.  ...  Considering the importance of breast cancer worldwide and the promising results reported by deep learning based methods in breast imaging, an overview of the recent state-of-the-art deep learning based  ...  infiltrating and the roles of each cell type in breast cancer initiation and progression.  ... 
doi:10.1016/j.media.2018.03.006 pmid:29679847 fatcat:nkrmtohwfvdtfpo3rbdvvotu2a

Semantic annotation for computational pathology: Multidisciplinary experience and best practice recommendations [article]

Noorul Wahab, Islam M Miligy, Katherine Dodd, Harvir Sahota, Michael Toss, Wenqi Lu, Mostafa Jahanifar, Mohsin Bilal, Simon Graham, Young Park, Giorgos Hadjigeorghiou, Abhir Bhalerao (+15 others)
2021 arXiv   pre-print
, ML experts and researchers as part of the Pathology image data Lake for Analytics, Knowledge and Education (PathLAKE) consortium.  ...  The annotation of important visual constructs in pathology images is an important component of CPath projects.  ...  of Oxfordall were involved in generating the PathLAKE programme, including funding.  ... 
arXiv:2106.13689v1 fatcat:pxqxt5jqx5hvddqq543olgi3dq

Accurate and reproducible invasive breast cancer detection in whole-slide images: A Deep Learning approach for quantifying tumor extent

Angel Cruz-Roa, Hannah Gilmore, Ajay Basavanhally, Michael Feldman, Shridar Ganesan, Natalie N.C. Shih, John Tomaszewski, Fabio A. González, Anant Madabhushi
2017 Scientific Reports  
In this study, we present a classification approach for detecting presence and extent of invasive breast cancer on whole slide digitized pathology images using a ConvNet classifier 38, 41, 42 .  ...  In the context of breast cancer pathology, a number of computational imaging approaches have been recently applied for problems such as (i) detection of mitoses 13-17 , tubules 18,19 , nuclei 19,20 , and  ...  Detection of tumor cells in a histologic section is the first step for the pathologist when diagnosing breast cancer (BCa).  ... 
doi:10.1038/srep46450 pmid:28418027 pmcid:PMC5394452 fatcat:pugi6kitebf7dmnb7zapkdamm4

Image analysis and machine learning in digital pathology: Challenges and opportunities

Anant Madabhushi, George Lee
2016 Medical Image Analysis  
The review ends with a brief discussion of some of the technical and computational challenges to be overcome and reflects on future opportunities for the quantitation of histopathology.  ...  The purpose of this review is to discuss developments in computational image analysis tools for predictive modeling of digital pathology images from a detection, segmentation, feature extraction, and tissue  ...  The ratio (ITLR) of ITLs to the total number of cancer cells was then calculated and found to be an independent prognostic predictor of disease-specific survival in two triple negative breast cancer cohorts  ... 
doi:10.1016/j.media.2016.06.037 pmid:27423409 pmcid:PMC5556681 fatcat:hkfeb37xbrbd3j4zu5h5cnga3q

A Deep Convolutional Neural Network for segmenting and classifying epithelial and stromal regions in histopathological images

Jun Xu, Xiaofei Luo, Guanhao Wang, Hannah Gilmore, Anant Madabhushi
2016 Neurocomputing  
In this work we compare DCNN based models with three handcraft feature extraction based approaches on two different datasets which consist of 157 Hematoxylin and Eosin (H&E) stained images of breast cancer  ...  and 1376 immunohistological (IHC) stained images of colorectal cancer, respectively.  ...  He is also the co-founder of Ibris Inc. a startup company focused on developing image based assays for breast cancer prognosis.  ... 
doi:10.1016/j.neucom.2016.01.034 pmid:28154470 pmcid:PMC5283391 fatcat:hvm7zmmz3jdy7jkrcnxz5stbae

Spectral Imaging and Pathology: Seeing More

Richard M. Levenson
2004 Laboratory medicine  
in a case of cancerization (infiltration of architecturally normal breast lobules by breast cancer cells).  ...  An example illustrating the benefit of spectral imaging on a clinical specimen of breast cancer is shown in I4.  ...  An H&E-stained breast lobule that had been partially infiltrated by cancer cells ("cancerization") was spectrally imaged from 440 to 700 nm in 10-nm steps using a 20x lens.  ... 
doi:10.1309/krnfwqqeuplql76l fatcat:7kqwq4fuuzburo2rl435ham7em

Spectral Imaging and Pathology: Seeing More

Richard M. Levenson
2004 Laboratory medicine  
in a case of cancerization (infiltration of architecturally normal breast lobules by breast cancer cells).  ...  An example illustrating the benefit of spectral imaging on a clinical specimen of breast cancer is shown in I4.  ...  An H&E-stained breast lobule that had been partially infiltrated by cancer cells ("cancerization") was spectrally imaged from 440 to 700 nm in 10-nm steps using a 20x lens.  ... 
doi:10.1309/krnf-wqqe-uplq-l76l fatcat:35spzp2grncjbfuztysa5nbcwe

Nuclear shape and orientation features from H&E images predict survival in early-stage estrogen receptor-positive breast cancers

Cheng Lu, David Romo-Bucheli, Xiangxue Wang, Andrew Janowczyk, Shridar Ganesan, Hannah Gilmore, David Rimm, Anant Madabhushi
2018 Laboratory Investigation  
Early-stage estrogen receptor-positive (ER+) breast cancer (BCa) is the most common type of BCa in the United States.  ...  This study aimed to investigate whether quantitative computer-extracted image features of nuclear shape and orientation on digitized images of hematoxylin-stained and eosin-stained tissue of lymph node-negative  ...  We also thank Tyler Smallman for his assistance with the digital image scanning and file management.  ... 
doi:10.1038/s41374-018-0095-7 pmid:29959421 pmcid:PMC6214731 fatcat:pil4q7g7ozcfhmaipxduolczr4

Temporal and spatial topography of cell proliferation in cancer [article]

Giorgio Gaglia, Sheheryar Kabraji, Danae Argyropoulou, Yang Dai, Shu Wang, Johann Bergholz, Shannon Coy, Jia-Ren Lin, Rinath Jeselsohn, Otto Metzger, Eric P Winer, Deborah A Dillon (+3 others)
2021 bioRxiv   pre-print
Proliferation is a fundamental trait of cancer cells but is poorly characterized in tumors by classical histologic methods.  ...  Multivariate measures capture clinically significant features of cancer proliferation, a fundamental step in enabling more precise use of anti-cancer therapies.  ...  the mitotic index reports for cells in M phase.  ... 
doi:10.1101/2021.05.16.443704 fatcat:43nav545qja2damd5iu67owsgm

Development and translational imaging of a TP53 porcine tumorigenesis model

Jessica C. Sieren, David K. Meyerholz, Xiao-Jun Wang, Bryan T. Davis, John D. Newell, Emily Hammond, Judy A. Rohret, Frank A. Rohret, Jason T. Struzynski, J. Adam Goeken, Paul W. Naumann, Mariah R. Leidinger (+6 others)
2014 Journal of Clinical Investigation  
For example, although breast carcinomas are the most frequent tumor observed in Li-Fraumeni patients, we did not detect any in this initial cohort.  ...  This is particularly true for cancer, for which imaging technologies and surgical procedures are instrumental in current detection and treatment plans.  ... 
doi:10.1172/jci75447 pmid:25105366 pmcid:PMC4151205 fatcat:wmwjcrsj45gjdmwz3f7joiwgm4

Polypeptidic Taxol-Tropins: Targeting paclitaxel to the tumor microenvironment

Erlinda M. Gordon, Seiya Liu, Sant P. Chawla, Frederick L. Hall, Auctores Publishing LLC
2021 Cancer Research and Cellular Therapeutics  
Importantly, the cytotoxic bioactivity of the Taxol-Tropin-bound-PTX molecule was well preserved in cellulo, as was demonstrated by cytocidal activity observed in MDA-MB-231 breast cancer cell cultures  ...  Further, the tumor targeting property of the Taxol-Tropin aptamers was tested in vivo in a murine model of metastatic cancer.  ...  Gordon, Art Consultant for Counterpoint Biomedica LLC, for graphic illustrations and assistance in manuscript writing. Copy rights@ Erlinda M. Gordon et.al.  ... 
doi:10.31579/2640-1053/089 fatcat:7y5fnup3vngzbmiqrpwamn7gye

Low Dimensional Representation of Fisher Vectors for Microscopy Image Classification

Yang Song, Qing Li, Heng Huang, Dagan Feng, Mei Chen, Weidong Cai
2017 IEEE Transactions on Medical Imaging  
Our method is evaluated on four publicly available microscopy image datasets of different imaging types and applications, including the UCSB breast cancer dataset, MICCAI 2015 CBTC challenge dataset, and  ...  Microscopy image classification is important in various biomedical applications, such as cancer subtype identification and protein localization for high content screening.  ...  Example images of each dataset are shown in Fig 1. 1) UCSB breast cancer dataset: Breast cancer is one of the most common types of cancer among women [59] .  ... 
doi:10.1109/tmi.2017.2687466 pmid:28358678 fatcat:rq76wyzscbgl3j3ajpjvqrsnmu

Clinically actionable mutation profiles in patients with cancer identified by whole-genome sequencing

Anna Schuh, Helene Dreau, Samantha J.L. Knight, Kate Ridout, Tuba Mizani, Dimitris Vavoulis, Richard Colling, Pavlos Antoniou, Erika M. Kvikstad, Melissa M. Pentony, Angela Hamblin, Andrew Protheroe (+13 others)
2018 Molecular Case Studies  
WGS results helped to clarify an uncertain histopathological diagnosis in one case, led to informed or supported prognosis in two cases, leading to de-escalation of therapy in one, and indicated potential  ...  Next-generation sequencing (NGS) efforts have established catalogs of mutations relevant to cancer development. However, the clinical utility of this information remains largely unexplored.  ...  The clinical utility and cost-effectiveness of targeted next-generation sequencing (TGS) cancer panel testing to detect somatically acquired single gene mutations is now established in specific disease  ... 
doi:10.1101/mcs.a002279 pmid:29610388 pmcid:PMC5880257 fatcat:dcevlikk55hdpacdaras2mhlpi

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Joel Saltz, Rajarsi Gupta, Le Hou, Tahsin Kurc, Pankaj Singh, Vu Nguyen, Dimitris Samaras, Kenneth R. Shroyer, Tianhao Zhao, Rebecca Batiste, John Van Arnam, Ilya Shmulevich (+729 others)
2018 Cell Reports  
Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment.  ...  Graphical Abstract Highlights d Deep learning based computational stain for staining tumorinfiltrating lymphocytes (TILs) d TIL patterns generated from 4,759 TCGA subjects (5,202 H&E slides), 13 cancer  ...  Bottom: these trained CNNs are then used on the full set of 5,455 images from 13 cancer types to generate TIL maps. During TIL map generation, a probability map for TILs is generated from each image.  ... 
doi:10.1016/j.celrep.2018.03.086 pmid:29617659 pmcid:PMC5943714 fatcat:2ypsyvcvyvdezk7tva3dogmcgi
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