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Glandular Segmentation of Prostate Cancer: An Illustration of How the Choice of Histopathological Stain Is One Key to Success for Computational Pathology

Christophe Avenel, Anna Tolf, Anca Dragomir, Ingrid B. Carlbom
2019 Frontiers in Bioengineering and Biotechnology  
Digital pathology offers the potential for computer-aided diagnosis, significantly reducing the pathologists' workload and paving the way for accurate prognostication with reduced inter-and intra-observer  ...  We address the effect of tissue preparation on glandular segmentation with an alternative stain, Picrosirius red-hematoxylin, which clearly delineates the stromal boundaries, and couple this stain with  ...  Pathologists rely on multiple, contrasting stains to analyze tissue samples, but histological stains are developed for analysis with a microscope and not for computational pathology applications.  ... 
doi:10.3389/fbioe.2019.00125 pmid:31334225 pmcid:PMC6624635 fatcat:efk45xglcrcubg62k4ckwzoo54

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

Anant Madabhushi, George Lee
2016 Medical Image Analysis  
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  ...  Image analysis and computer assisted detection and diagnosis tools previously developed in the context of radiographic images are woefully inadequate to deal with the data density in high resolution digitized  ...  Segmentation and detection of histologic primitives The recent advent of digital whole slide scanners has allowed for the development of quantitative histomorphometry (QH) analysis approaches which can  ... 
doi:10.1016/j.media.2016.06.037 pmid:27423409 pmcid:PMC5556681 fatcat:hkfeb37xbrbd3j4zu5h5cnga3q

Automatic classification of prostate stromal tissue in histological images using Haralick descriptors and Local Binary Patterns

D L L Oliveira, M Z Nascimento, L A Neves, V R Batista, M F Godoy, R S Jacomini, Y A S Duarte, P F F Arruda, D S Neto
2014 Journal of Physics, Conference Series  
The system was tested in 105 prostate images, which were divided into three groups of 35 images: normal, hyperplastic and cancerous.  ...  The system performance was evaluated using the area under the ROC curve and resulted in 0.98 for normal versus cancer, 0.95 for hyperplasia versus cancer and 0.96 for normal versus hyperplasia.  ...  Conclusion In this paper an automatic classification method was proposed to analyse prostate stromal tissue of normal, hyperplastic and cancer images.  ... 
doi:10.1088/1742-6596/490/1/012151 fatcat:qf55kescnnd7tbpn5dyhvrywsi

Ductal adenocarcinoma of the prostate: immunohistochemical findings and clinical significance

Yiran Huang, Sha, Bo, Pan, Zhang, Xuan, Chen, Li, Wang, Liu
2013 OncoTargets and Therapy  
The level of prostate-specific antigen (PSA) before and after surgery was assessed. Different prostate cancer markers were used for immunohistochemical staining.  ...  Immunohistochemical staining results of the prostatic ductal adenocarcinoma confirmed positivity for PSA, prostatic acid phosphatase, androgen receptor, and alpha-methyacyl co-enzyme A (CoA)-reductase  ...  Acknowledgment This study was supported by National Natural Science Foundation of the People's Republic of China (91129725). Disclosure The authors report no conflicts of interest in this work.  ... 
doi:10.2147/ott.s47165 pmid:24187500 pmcid:PMC3810445 fatcat:x7rilxhjl5h5bo6yc7uuumzlce

Study of Computerized Segmentation & Classification Techniques: An Application to Histopathological Imaginary

Pranshu Saxena, Anjali Goyal
2019 Informatica (Ljubljana, Tiskana izd.)  
The main goal of this study is to understand and address the challenges associated with the development of image analysis techniques for computer-aided interpretation of histopathology imagery.  ...  This paper reviews recent state of the art technology for histopathology and briefly describes the recent development in histology and its application towards quantifying the perceptive issue in the domain  ...  A study by Teot et al. in 2007 [24] shows that for NB diagnosis, this Gleason scale for prostate cancer Quantitative image analysis in the context of prostate cancer is done with the help of gleason  ... 
doi:10.31449/inf.v43i4.2142 fatcat:wkqlu2h6fjcuxckqltjrtpkgai

Automated analysis of co-localized protein expression in histologic sections of prostate cancer

Thomas A. Tennill, Mitchell E. Gross, Hermann B. Frieboes, Robert Hurst
2017 PLoS ONE  
prostate cancer.  ...  Expression of two markers was chosen to represent stromal (CD31) and epithelial (Ki-67) compartments in prostate cancer.  ...  In conclusion, an approach was developed for automated analysis of co-localized protein expression in histologic sections of prostate cancer, and initially evaluated it with three types of patient histology  ... 
doi:10.1371/journal.pone.0178362 pmid:28552967 pmcid:PMC5446169 fatcat:wjbxsiuxrjhnjm3bernjicn4ym

Role of AI and Histopathological Images in Detecting Prostate Cancer: A Survey

Sarah M. Ayyad, Mohamed Shehata, Ahmed Shalaby, Mohamed Abou El-Ghar, Mohammed Ghazal, Moumen El-Melegy, Nahla B. Abdel-Hamid, Labib M. Labib, H. Arafat Ali, Ayman El-Baz
2021 Sensors  
One of the ways to accelerate such an analysis is by employing artificial intelligence (AI) through the use of computer-aided diagnosis (CAD) systems.  ...  Histopathological image diagnosis is a gold standard for detecting prostate cancer as it has different visual characteristics but interpreting those type of images needs a high level of expertise and takes  ...  Acknowledgments: Authors like to acknowledge the support of the Academy of Scientific Research and Technology in Egypt in this work.  ... 
doi:10.3390/s21082586 pmid:33917035 fatcat:qfspvswivrbnlaih5y4gun5zwm

Medical Datasets Collections for Artificial Intelligence-based Medical Image Analysis [article]

Yang Wen
2021 arXiv   pre-print
We collected 32 public datasets, of which 28 for medical imaging and 4 for natural images, to conduct study.  ...  The images of these datasets are captured by different cameras, thus vary from each other in modality, frame size and capacity.  ...  In GlaS challenge, participants are encouraged to run their gland segmentation algorithms on images of Hematoxylin and Eosin (H&E) stained slides.  ... 
arXiv:2102.01549v3 fatcat:4vj7uh7b45b7rcsxqb2hptvehi

Histopathological Image Analysis: A Review

M.N. Gurcan, L.E. Boucheron, A. Can, A. Madabhushi, N.M. Rajpoot, B. Yener
2009 IEEE Reviews in Biomedical Engineering  
Analogous to the role of computer-assisted diagnosis (CAD) algorithms in medical imaging to complement the opinion of a radiologist, CAD algorithms have begun to be developed for disease detection, diagnosis  ...  Over the past decade, dramatic increases in computational power and improvement in image analysis algorithms have allowed the development of powerful computer-assisted analytical approaches to radiological  ...  [126] have been developing computerized detection methods for prostate cancer from high-resolution multimodal MRI .  ... 
doi:10.1109/rbme.2009.2034865 pmid:20671804 pmcid:PMC2910932 fatcat:a6sm4iy5gffbhlc23dtlp7xe2q

Going Deeper through the Gleason Scoring Scale: An Automatic end-to-end System for Histology Prostate Grading and Cribriform Pattern Detection

Julio Silva-Rodríguez, Adrián Colomer, María A. Sales, Rafael Molina, Valery Naranjo
2020 Computer Methods and Programs in Biomedicine  
In recent years, with the development of digitisation devices, the use of computer vision techniques for the analysis of biopsies has increased.  ...  Prostate cancer is one of the most common diseases affecting men worldwide. The Gleason scoring system is the primary diagnostic and prognostic tool for prostate cancer.  ...  These are based on the digitisation of the histological crystals, obtaining whole slide images (WSIs) and developing computer vision algorithms to detect the cancerous regions inside the biopsy (or WSI  ... 
doi:10.1016/j.cmpb.2020.105637 pmid:32653747 fatcat:txoi2flhjrdidkyiqmzmdrkfry

Multimodal microscopy for automated histologic analysis of prostate cancer

Jin Tae Kwak, Stephen M Hewitt, Saurabh Sinha, Rohit Bhargava
2011 BMC Cancer  
Prostate cancer is the single most prevalent cancer in US men whose gold standard of diagnosis is histologic assessment of biopsies.  ...  Manual assessment of stained tissue of all biopsies limits speed and accuracy in clinical practice and research of prostate cancer diagnosis.  ...  The project was also supported by a DoD prostate cancer research program young investigator award (to R.B.) and a computational science and engineering (CSE) fellowship (to J.T.K). Author details  ... 
doi:10.1186/1471-2407-11-62 pmid:21303560 pmcid:PMC3045985 fatcat:dr7ungnvsbfj5nehhrjurqrgsu

Multi-Features Classification of Prostate Carcinoma Observed in Histological Sections: Analysis of Wavelet-Based Texture and Colour Features

Bhattacharjee, Kim, Park, Prakash, Madusanka, Cho, Choi
2019 Cancers  
In this study, biopsy images are used for histological grading and the analysis of benign and malignant prostate tissues.  ...  In order to analyse and classify the histological grades of prostate carcinomas, pixel-based colour moment descriptor (PCMD) and gray-level co-occurrence matrix (GLCM) methods were used to extract the  ...  [34] developed a computer-aided diagnosis system for the automatic grading of histological images of PCa tissue. Their system is based on 2D discrete wavelet packet decomposition and SVM.  ... 
doi:10.3390/cancers11121937 pmid:31817111 pmcid:PMC6966617 fatcat:crz3keliqzhqxite644bzzurru

Segmentation methods of H&E-stained histological images of lymphoma: A review

Thaína A. Azevedo Tosta, Leandro A. Neves, Marcelo Z. do Nascimento
2017 Informatics in Medicine Unlocked  
A B S T R A C T Image processing techniques are being widely developed for helping specialists in analysis of histological images obtained from biopsies for diagnoses and prognoses determination.  ...  Thus, the progressive development of histological images segmentation is an important step for modern medicine.  ...  To diagnose NHL, a specialist analyses tissue samples stained with, for example, hematoxylin-eosin (H&E) to identify cancerous regions.  ... 
doi:10.1016/j.imu.2017.05.009 fatcat:kn26dm5ysfft7g6pi5p6xlob7u

Exploring Genetic-histologic Relationships in Breast Cancer [article]

Ruchi Chauhan, PK Vinod, CV Jawahar
2021 arXiv   pre-print
The advent of digital pathology presents opportunities for computer vision for fast, accurate, and objective solutions for histopathological images and aid in knowledge discovery.  ...  We also gain insights that can serve as hypotheses for further experimentations, including the presence of lymphocytes and karyorrhexis.  ...  INTRODUCTION Histopathological evaluation involving microscopic examination of Hematoxylin & Eosin (H&E) stained specimen on the glass slide is considered a gold standard for cancer diagnosis.  ... 
arXiv:2103.08082v1 fatcat:getvntkuirfupavquii3uqsrny

Histological images segmentation of mucous glands [article]

A. Khvostikov, A. Krylov, O. Kharlova, N. Oleynikova, I. Mikhailov, P. Malkov
2018 arXiv   pre-print
We review major trends in histological images segmentation and design a new convolutional neural network for mucous gland segmentation.  ...  Accurate segmentation of mucous glands from histology images is a crucial step to obtain reliable morphometric criteria for quantitative diagnostic methods.  ...  The dataset provides 165 Hematoxylin and Eosin (H&E) stained slides, consisting of a variety of histological grades.  ... 
arXiv:1806.07781v1 fatcat:bifrfmermrfgdklziql5cqunl4
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