Developing Deep Learning Models for Pathology Analysis
Posted 9th March 2020 by Liv Sewell
Ahead of the 6th Digital Pathology & AI Congress: USA, Dr Saeed Hassanpour introduces us to the subject of his presentation: the opportunities and challenges in developing deep learning based tools for histology.
Inspirata and Cirdan Announce New Technical Partnership at the Digital Pathology & AI Congress
Posted 18th December 2019 by Joshua Sewell
At the 6th Digital Pathology & AI Congress, Inspirata and Cirdan announced their new technical partnership designed to empower NHS clinical laboratories to accelerate their use of digital pathology.
3 Ways Single-Cell Sequencing and AI are Transforming Kidney Transplantation
Posted 27th November 2019 by Liv Sewell
Transplantation is now a successful therapy for end-stage renal disease (ESRD). The first successful kidney transplantation happened in Boston in 1954 and the procedure is now routine clinical practice in more than 80 countries worldwide.
Ishita Moghe and Kim Solez outline some of the major strides taken in kidney pathology and transplantation through the use of scRNA-seq and Artificial Intelligence (AI).
How will Ground Truth Colour Standardisation yield the benefits of AI in Medical Imaging?
Posted 6th November 2019 by Joshua Sewell
The essence of colour management is to ensure that the original target translates through a digital pathway so that the output images are exactly the same colour as the original.
When applied to medical imaging, and considering all the specific stains used in pathology, colour management becomes important. Particular coloured stains bind specific structures of cells in tissue to confer visualisation of diagnostic information. Without translating the colour through the digital pathway correctly, you lose the aspect of diagnostic information, which comes from specific colours.
Machine Learning Innovation to aid Clinical Decision Making in Pathology
Posted 1st November 2019 by Joshua Sewell
“A medical image alone doesn’t add value unless it is tied to a clinical decision-making process” – Jochen Lennerz
The Breast Cancer Scanning Initiative (BCSI) scans histological slides of patients with high-risk breast lesions to generate annotated images. We then apply a Machine Learning algorithm to the slides to determine whether surgery is necessary.
Reshaping drug discovery with deep learning and polypharmacology
Posted 23rd October 2019 by Joshua Sewell
Cyclica is a Toronto-based biotech that leverages artificial intelligence and computational biophysics to reshape the drug discovery process. We spoke to their Chief Scientific Officer Andreas Windemuth.
Bridging the gap between pathologist and algorithm
Posted 16th October 2019 by Liv Sewell
Could AI replace pathologists? As we look forward to the 6th Digital Pathology and AI Congress: Europe on the 5th – 6th December 2019, we look back at Dr Hamid Tizhoosh’s keynote presentation from last year.
Pixel analysis: the new era of digital pathology
Posted 9th October 2019 by Liv Sewell
Professor David Snead is leading the implementation of digital pathology for Coventry and Warwickshire Pathology Services and directs one of the five Government funded centres in the UK pioneering AI and image diagnostics integration. His main research interests lie in extending the capability of digital pathology for routine diagnostic use and the advancement and deployment of computer assisted diagnostic algorithms. In this third highlight from the conference we revisit Professor Snead’s presentation to get a clinical perspective on how deep learning and artificial intelligence (AI) are set to play an increasing role in daily practice.