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Optimization Calculation of Medical Staining Process Based on Autostainer

Published: 01 June 2024 Publication History

Abstract

Based on the current mainstream pathological staining methods, this paper studies and designs a scheduling method applied to the pathological autostainer process. The staining process performed by the pathological autostainer is based on clinical pathological standards, and a series of continuous staining operations are carried out on pathological slices. The operation process should follow a fixed staining stage. The pathologically required stained slices were strictly immersed in the corresponding reagents to achieve the demand of staining dehydration. According to the characteristics of different reagents, the staining process has high requirements in the staining time accuracy of pathological slices. The scheduling method in this paper builds a mathematical model of the staining process of the autostainer according to the time characteristics of the staining process, and uses the Simulated Annealing Algorithm to obtain the minimum total staining time under the input of multiple slices. Through the simulation of experimental data, the algorithm was analyzed and proved to be effective for the pathological staining process.

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CVDL '24: Proceedings of the International Conference on Computer Vision and Deep Learning
January 2024
506 pages
ISBN:9798400718199
DOI:10.1145/3653804
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

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Published: 01 June 2024

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