AI-Driven Pathological Image Diagnosis
for all medical practitioners around the world
Digital Pathology AI Analysis Solution 「PidPort」
To shape a more comfortable medical environment for all healthcare and medical professionals around the world.
Through our proprietary image processing technology driven by Deep Learning/AI, PidPort provides highly accurate and rapid pathological screening, as well as telepathology function. By leveraging the power of technology, we can create a medical environment that enables a more efficient and accurate pathological diagnosis and better management of the ever-increasing burden of medical sites with an AI-driven pathological image analysis.
PidPort’s three features. Eliminate concerns about physical space needed for the storage and management of pathology specimen slides, alleviate diagnosis workflow, and achieve efficiency through remote diagnosis.(※)
Digitization enables cloud-based management and storage of pathologic image data and case histories without the need to worry about deterioration or physical storage space.
PidPort’s telepathology (remote pathological diagnosis) function enables optimal, timely pathological diagnosis requests and support via a network of medical practitioners around the world.
PidPort enables highly precise and instantaneous screening of pathologic tissue and cells using AI independently developed by Medmain. As an assistant to medical practitioners, the system eases one’s daily workflow.
※It is depending on the country and region, all or a certain feature are available for use. Please contact us for details.
Once pathological specimens are digitized, AI screening analysis, telepathology, and image data storage services are all available as one.
(It is possible to provide only necessary features according to your needs, also It is depending on the country and region,
all or a certain feature are available for use. Please contact us for details. )
Instantly access specimen information / Eliminate physical storage space / Smoothly manage and store pathology image data and case information
Efficient pathological diagnosis work / Smoothly manage and store pathology image data and case information
No need to physically move or send pathological specimen / Timely information sharing between pathologists
Below are the types of organs and evaluation methods of the models we have developed.
We plan to proceed with R&D on other organs, such as pancreas (histology).
Deep learning models for histopathological classification of gastric
and colonic epithelial tumors
Osamu Iizuka*１, Fahdi Kanavati*１, Kei Kato*1, Michael Rambeau*1, Koji Arihiro*2 & Masayuki Tsuneki*１
1)Medmain Inc. 2) Department of Anatomical Pathology, Hiroshima University Hospital
Published: 30 Jan, 2020 Scientific Reports