Summary ALOVAS Platform:
ALOVAS acts as an A.I. Pathology Platform which provides high resolution pathology image viewer. Even Giga-pixel-level original images can be viewed online in real time. ALOVAS platform can be used not only on computer, but also on iPad. Users can upload images on the platform and select AI models for automated detection, and browse the detection results on the platform. ALOVAS also provides commonly used annotation tools, including hand-drawing, dots, rectangles, etc., which can be used to mark areas of interest. Embedded with the ALOVAS platform also provided several detection algorithms. We hope ALOVAS can assist physicians in rapid diagnosis, in related pathological research, and reduce the workload of pathologists in the future.

Provided Detection Algorithms:

- Tumor Detection and Grading
- Hepatitis Staging
- Lipid Droplet Detection

Tumor Detection and Grading:
A multi-scale convolutional neural network is utilized for patch-wise recognition of liver tumor with a detection performance of 95% mIOU. After the tumor is identified, the area is fed into another classifier for grading liver tissue as one of four different tumor grades. It combines a traditional image-processing based extractor retrieving sinusoid, cell and trabecular features as well as an CNN based extractor retrieving tissue features to achieve 89% grading accuracy.

Hepatitis Staging:
A framework is proposed to automate the calculation of Ishak Score for quantifying the degree of liver fibrosis. Ambiguous descriptions from human judgement can be therefore avoided in hepatitis diagnosis.
Technical Film
Keyword ALOVAS Platform Tumor Detection and Grading Hepatitis Staging
Research Project
Research Team
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