Work

Synthesizing whole slide images

Year: 2015

Type: conference-paper

Abstract: The increasing availability of digital whole slide images opens new perspectives for computer-assisted image analysis complementing modern histopathology, assuming we can implement reliable and efficient image analysis algorithms to extract the biologically relevant information. Both validation and supervised learning techniques typically rely on ground truths manually made by human experts. However, this task is difficult, subjective and usually not exhaustive. This is a well-known issue in the field of biomedical imaging, and a common solution is the use of artificial “phantoms”. Following this trend, we study the feasibility of synthesizing artificial histological images to create perfect ground truths. In this paper, we show that it is possible to generate a synthetic whole slide image with reasonable computing resources, and we propose a way to evaluate its quality.

Source: International symposium on image and signal processing and analysis/ISPA ...

DOI: 10.1109/ispa.2015.7306050

Authors: Gregory Apou, Friedrich Feuerhake, Germain Forestier, Benoit Naegel, Cedric Wemmert

Institutions: Laboratoire des Sciences de l'Ingénieur, de l'Informatique et de l'Imagerie, Université de Strasbourg, Medizinische Hochschule Hannover, Université de Haute-Alsace

Language: English

Topic: AI in cancer detection

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funder: Bundesministerium für Bildung und Forschung

OpenAlex ID: W1961684045

FWCI: 0.188

Cites: 22

Cited by: 9

Related to: 10