FREE COURSE about HistoSuite Tools

How Every Digital Pathology Trailblazer Can Control Slide Quality Consistently & Efficiently Develop Tissue Image Analysis Models with Amazing Performance

FOR FREE with Open-Source Suite of Digital Pathology Tools

Why you CANNOT MISS this HistoQC Course?

Are you tired of sorting through all kinds of stain variations, slide preparation and scanning artifacts manually in your pathology image dataset? Afraid that the trend you identified in your image data is actually a reflection of a batch effect? Or maybe you just want to stop wasting time on useless annotations and know exactly which patches are relevant for your model development? No, not that either? How about keeping you H&E staining consistent in your lab?

If you resonate with any of the above, THIS COURSE is a MUST, because we have FREE tools to solve your problems!


FREE Tools for Computational Pathology!


HistoBlur is a deep learning-based tool that allows for the fast and accurate detection of blurry regions in Whole Slide Images.

Quick Annotator

An open-source digital pathology tool for rapidly annotating objects.


Open-source tool for generation of reproducible slide quality metrics with artifact localization.

Cohort Finder

Intelligent data partitioning tool that uses quality control metrics. It helps you identify batch effects, design the ideal model training/ test and validation set and can increase the performance and generalizability of machine learning model.

Patch Sorter

Patch Sorter is an open-source digital pathology tool for histologic object labeling. It helps you annotate fast exactly the right patches to train your model.

About Your Speakers

Aleksandra Zuraw, DVM, Ph

Dr. Zuraw is a veterinary pathologist actively involved in tissue image analysis work since entering the field of digital pathology in 2016.

She is a digital pathologist practicing pathology on digital slides. Because of the impact digital pathology has on patient care and her life, her mission is to PROMOTE DIGITAL PATHOLOGY IN THE SCIENTIFIC COMMUNITY with her blog, podcast and social media presence and bridge the gap between pathology and computer science.

She also likes walking around and taking pictures.

Andrew Janowczyk, PhD

Dr. Andrew Janowczyk’s research focuses on applying computer vision and machine learning algorithms to digital pathology images including algorithms helping with disease detection and cancer grading. His newer research focuses on the tasks of predicting prognosis and therapy response in the oncology domain. His recent ITCR R01grant aims to develop open-source tools to facilitate cancer research through improved quality control, annotation, and identification of slides for sophisticated machine learning algorithms.Headline

He also likes cooking, and mountain stuff.

FREE COURSE about HistoSuite Tools

Stop wasting time and start optimizing your pathology image dataset today! Join our FREE course and gain access to powerful tools that will eliminate the hassle of manual sorting, batch effects, useless annotations, and inconsistent staining. Don't miss out on this opportunity to take your model development to the next level. Enroll now and revolutionize your pathology research!

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© 2023 Digital Pathology Place

© 2023 Digital Pathology Place