Digital Pathology

5 Ways to Make Histopathology Image Models More Robust to Domain Shifts: Exploring a variety of approaches: stain normalization, color augmentation, adversarial domain adaptation, model adaptation, and finetuning

Digital Pathology & AI in routine clinical practice:From quality control to primary cancer diagnosis

https://www.youtube.com/watch?v=7pRmonus9iM

Microvisioneer

Argenit

X-WOW

QuPath

Mac OS için.svsdosyalarını açacak program ararken bulmuştum QuPath'ı.

QuPath'ın validasyonu kolon tümörlerinde CD3, CD8, p53 ve PD-L1 skorlaması yanısıra H&E preparatlarındaki tümör-stroma oranı ile yapılmış. Örnekler TMA üzerinde, kod ile ve otomatik analiz ile skorlanmış. Önemli bir nokta skorlamalar sağ kalım ile de karşılaştırılmış.

QuPath: Open source software for digital pathology image analysis Scientific Reports volume 7, Article number: 16878 (2017) doi:10.1038/s41598-017-17204-5

QuPath'ın oldukça iyi eğitim dökümanları var:

https://github.com/qupath/qupath/wiki

Makaledeki videolar şunlar:

MOESM2_ESM.mov

MOESM3_ESM.mov

Makalenin referans verdiği diğer dijital analiz araçlarının makaleleri ise şunlar:

• NIH Image to ImageJ: 25 years of image analysis

• Fiji: an open-source platform for biological-image analysis

• Icy: an open bioimage informatics platform for extended reproducible research

• CellProfiler™: free, versatile software for automated biological image analysis

• OpenSlide: A vendor-neutral software foundation for digital pathology

• SlideToolkit: An Assistive Toolset for the Histological Quantification of Whole Slide Images

• Collaborative analysis of multi-gigapixel imaging data using Cytomine

• Immunoratio 'yu rutin tanılarda ben kullanıyordum. Elbette tanı için direk oradaki çıkan sayıyı vermiyordum ama kendimi eğitmek için iyi bir araçtı. Immunomembrane 'den ise pek iyi sonuç alamamıştım.

• ImmunoRatio: a publicly available web application for quantitative image analysis of estrogen receptor (ER), progesterone receptor (PR), and Ki-67

https://digitalpathologyassociation.org/whole-slide-imaging-repository

https://digitalpathologyassociation.org/

• Websites

https://pathpresenter.com/

http://www.rosaicollection.org/

http://cancer.digitalslidearchive.net/

Cancer Digital Slide Archive: an informatics resource to support integrated in silico analysis of TCGA pathology data

https://academic.oup.com/jamia/article/20/6/1091/703483

• Johns Hopkins Pathology Unknowns

https://digital.pathology.johnshopkins.edu/repos/451

• Softwares

http://www.virasoft.com.tr/

http://en.mydigipath.com/

https://qupath.github.io/

http://www.microvisioneer.com/

http://virtualvizyon.com/

https://easyzoom.com/

• Easy Scanner

https://twitter.com/argenitt/status/814824189345624064

• Smartphone Whole Slide Imaging(sWSI) Demo--Low Cost Slide Scanner.

https://www.youtube.com/watch?v=orcYKy19mjQ

https://micro-manager.org/

• Google's interest in digital pathology is very important for our field. See 55th minute

https://youtu.be/Y2VF8tmLFHw?t=55m11s

• Assisting Pathologists in Detecting Cancer with Deep Learning

https://research.googleblog.com/2017/03/assisting-pathologists-in-detecting.html

• Detecting Cancer Metastases on Gigapixel Pathology Images

https://arxiv.org/abs/1703.02442

• Manual Microscope Image Stitching

https://www.meyerinst.com/digital/image-stitching/

• Motic EASY SCAN PRO Pathology Slide Scanner

https://www.meyerinst.com/motic-easy-scan-pro-digital-slide-scanner/

https://www.viewsiq.com/panoptiq

• Metadata matters: access to image data in the real world

http://jcb.rupress.org/content/189/5/777

• Detecting cancer in real-time with machine learning

https://www.youtube.com/watch?v=9Mz84cwVmS0

An Augmented Reality Microscope for Cancer Detection

An Augmented Reality Microscope for Real-time Automated Detection of Cancer

• Whole Slide Imaging Versus Microscopy for Primary Diagnosis in Surgical Pathology: A Multicenter Blinded Randomized Noninferiority Study of 1992 Cases (Pivotal Study).

http://journals.lww.com/ajsp/Abstract/publishahead/Whole_Slide_Imaging_Versus_Microscopy_for_Primary.97978.aspx

• The Gold Standard Paradox in Digital Image Analysis Manual Versus Automated Scoring as Ground Truth

Arch Pathol Lab Med. 2017 May 30. PMID: 28557614 DOI: 10.5858/arpa.2016-0386-RA

About the Usage of Digital Pathology

• Whole Slide Imaging Versus Microscopy for Primary Diagnosis in Surgical Pathology: A Multicenter Blinded Randomized Noninferiority Study of 1992 Cases (Pivotal Study).

http://journals.lww.com/ajsp/Abstract/publishahead/Whole_Slide_Imaging_Versus_Microscopy_for_Primary.97978.aspx

• The Gold Standard Paradox in Digital Image Analysis Manual Versus Automated Scoring as Ground Truth

Arch Pathol Lab Med. 2017 May 30. PMID: 28557614 DOI: 10.5858/arpa.2016-0386-RA

• Whole Slide Imaging Versus Microscopy for Primary Diagnosis in Surgical Pathology: A Multicenter Blinded Randomized Noninferiority Study of 1992 Cases (Pivotal Study).

http://journals.lww.com/ajsp/Abstract/publishahead/Whole_Slide_Imaging_Versus_Microscopy_for_Primary.97978.aspx

• The Gold Standard Paradox in Digital Image Analysis Manual Versus Automated Scoring as Ground Truth

Arch Pathol Lab Med. 2017 May 30. PMID: 28557614 DOI: 10.5858/arpa.2016-0386-RA

• Whole Slide Imaging Versus Microscopy for Primary Diagnosis in Surgical Pathology: A Multicenter Blinded Randomized Noninferiority Study of 1992 Cases (Pivotal Study).

http://journals.lww.com/ajsp/Abstract/publishahead/Whole_Slide_Imaging_Versus_Microscopy_for_Primary.97978.aspx

• The Gold Standard Paradox in Digital Image Analysis Manual Versus Automated Scoring as Ground Truth

Arch Pathol Lab Med. 2017 May 30. PMID: 28557614 DOI: 10.5858/arpa.2016-0386-RA

Digital Pathology

Mac OS için.svsdosyalarını açacak program ararken bulmuştum QuPath'ı.

QuPath'ın validasyonu kolon tümörlerinde CD3, CD8, p53 ve PD-L1 skorlaması yanısıra H&E preparatlarındaki tümör-stroma oranı ile yapılmış. Örnekler TMA üzerinde, kod ile ve otomatik analiz ile skorlanmış. Önemli bir nokta skorlamalar sağ kalım ile de karşılaştırılmış.

QuPath: Open source software for digital pathology image analysis Scientific Reports volume 7, Article number: 16878 (2017) doi:10.1038/s41598-017-17204-5

QuPath'ın oldukça iyi eğitim dökümanları var:

https://github.com/qupath/qupath/wiki

Makaledeki videolar şunlar:

MOESM2_ESM.mov

MOESM3_ESM.mov

Makalenin referans verdiği diğer dijital analiz araçlarının makaleleri ise şunlar:

• NIH Image to ImageJ: 25 years of image analysis

• Fiji: an open-source platform for biological-image analysis

• Icy: an open bioimage informatics platform for extended reproducible research

• CellProfiler™: free, versatile software for automated biological image analysis

• OpenSlide: A vendor-neutral software foundation for digital pathology

• SlideToolkit: An Assistive Toolset for the Histological Quantification of Whole Slide Images

• Collaborative analysis of multi-gigapixel imaging data using Cytomine

• Immunoratio 'yu rutin tanılarda ben kullanıyordum. Elbette tanı için direk oradaki çıkan sayıyı vermiyordum ama kendimi eğitmek için iyi bir araçtı. Immunomembrane 'den ise pek iyi sonuç alamamıştım.

• ImmunoRatio: a publicly available web application for quantitative image analysis of estrogen receptor (ER), progesterone receptor (PR), and Ki-67

https://digitalpathologyassociation.org/whole-slide-imaging-repository

https://digitalpathologyassociation.org/

• Websites

https://pathpresenter.com/

http://www.rosaicollection.org/

http://cancer.digitalslidearchive.net/

Cancer Digital Slide Archive: an informatics resource to support integrated in silico analysis of TCGA pathology data

https://academic.oup.com/jamia/article/20/6/1091/703483

• Johns Hopkins Pathology Unknowns

https://digital.pathology.johnshopkins.edu/repos/451

• Softwares

http://www.virasoft.com.tr/

http://en.mydigipath.com/

https://qupath.github.io/

http://www.microvisioneer.com/

http://virtualvizyon.com/

https://easyzoom.com/

• Easy Scanner

https://twitter.com/argenitt/status/814824189345624064

• Smartphone Whole Slide Imaging(sWSI) Demo--Low Cost Slide Scanner.

https://www.youtube.com/watch?v=orcYKy19mjQ

https://micro-manager.org/

• Google's interest in digital pathology is very important for our field. See 55th minute

https://youtu.be/Y2VF8tmLFHw?t=55m11s

• Assisting Pathologists in Detecting Cancer with Deep Learning

https://research.googleblog.com/2017/03/assisting-pathologists-in-detecting.html

• Detecting Cancer Metastases on Gigapixel Pathology Images

https://arxiv.org/abs/1703.02442

• Manual Microscope Image Stitching

https://www.meyerinst.com/digital/image-stitching/

• Motic EASY SCAN PRO Pathology Slide Scanner

https://www.meyerinst.com/motic-easy-scan-pro-digital-slide-scanner/

https://www.viewsiq.com/panoptiq

• Metadata matters: access to image data in the real world

http://jcb.rupress.org/content/189/5/777

• Detecting cancer in real-time with machine learning

https://www.youtube.com/watch?v=9Mz84cwVmS0

An Augmented Reality Microscope for Cancer Detection

An Augmented Reality Microscope for Real-time Automated Detection of Cancer

Mac OS için.svsdosyalarını açacak program ararken bulmuştum QuPath'ı.

QuPath'ın validasyonu kolon tümörlerinde CD3, CD8, p53 ve PD-L1 skorlaması yanısıra H&E preparatlarındaki tümör-stroma oranı ile yapılmış. Örnekler TMA üzerinde, kod ile ve otomatik analiz ile skorlanmış. Önemli bir nokta skorlamalar sağ kalım ile de karşılaştırılmış.

QuPath: Open source software for digital pathology image analysis Scientific Reports volume 7, Article number: 16878 (2017) doi:10.1038/s41598-017-17204-5

QuPath'ın oldukça iyi eğitim dökümanları var:

https://github.com/qupath/qupath/wiki

Makaledeki videolar şunlar:

MOESM2_ESM.mov

MOESM3_ESM.mov

Makalenin referans verdiği diğer dijital analiz araçlarının makaleleri ise şunlar:

• NIH Image to ImageJ: 25 years of image analysis

• Fiji: an open-source platform for biological-image analysis

• Icy: an open bioimage informatics platform for extended reproducible research

• CellProfiler™: free, versatile software for automated biological image analysis

• OpenSlide: A vendor-neutral software foundation for digital pathology

• SlideToolkit: An Assistive Toolset for the Histological Quantification of Whole Slide Images

• Collaborative analysis of multi-gigapixel imaging data using Cytomine

• Immunoratio 'yu rutin tanılarda ben kullanıyordum. Elbette tanı için direk oradaki çıkan sayıyı vermiyordum ama kendimi eğitmek için iyi bir araçtı. Immunomembrane 'den ise pek iyi sonuç alamamıştım.

• ImmunoRatio: a publicly available web application for quantitative image analysis of estrogen receptor (ER), progesterone receptor (PR), and Ki-67

https://digitalpathologyassociation.org/whole-slide-imaging-repository

https://digitalpathologyassociation.org/

• Websites

https://pathpresenter.com/

http://www.rosaicollection.org/

http://cancer.digitalslidearchive.net/

Cancer Digital Slide Archive: an informatics resource to support integrated in silico analysis of TCGA pathology data

https://academic.oup.com/jamia/article/20/6/1091/703483

• Johns Hopkins Pathology Unknowns

https://digital.pathology.johnshopkins.edu/repos/451

• Softwares

http://www.virasoft.com.tr/

http://en.mydigipath.com/

https://qupath.github.io/

http://www.microvisioneer.com/

http://virtualvizyon.com/

https://easyzoom.com/

• Easy Scanner

https://twitter.com/argenitt/status/814824189345624064

• Smartphone Whole Slide Imaging(sWSI) Demo--Low Cost Slide Scanner.

https://www.youtube.com/watch?v=orcYKy19mjQ

https://micro-manager.org/

• Google's interest in digital pathology is very important for our field. See 55th minute

https://youtu.be/Y2VF8tmLFHw?t=55m11s

• Assisting Pathologists in Detecting Cancer with Deep Learning

https://research.googleblog.com/2017/03/assisting-pathologists-in-detecting.html

• Detecting Cancer Metastases on Gigapixel Pathology Images

https://arxiv.org/abs/1703.02442

• Manual Microscope Image Stitching

https://www.meyerinst.com/digital/image-stitching/

• Motic EASY SCAN PRO Pathology Slide Scanner

https://www.meyerinst.com/motic-easy-scan-pro-digital-slide-scanner/

https://www.viewsiq.com/panoptiq

• Metadata matters: access to image data in the real world

http://jcb.rupress.org/content/189/5/777

• Detecting cancer in real-time with machine learning

https://www.youtube.com/watch?v=9Mz84cwVmS0

An Augmented Reality Microscope for Cancer Detection

An Augmented Reality Microscope for Real-time Automated Detection of Cancer

• Single slide scanner

optiscan