Development of a Transfer Learning-Based Interactive Tool for Pathological Image Tissue Segmentation

Authors

Institutions

Publication Details

Journal
Journal of Japan Society for Fuzzy Theory and Intelligent Informatics
Published
2026-02-14
DOI
https://doi.org/10.3156/jsoft.38.1_511
Primary Topic
Medical Image Segmentation Techniques
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Development of a Transfer Learning-Based Interactive Tool for Pathological Image Tissue Segmentation

Takeshi Terazawa, Toshiya Arakawa, Hoshiro SATO
Journal of Japan Society for Fuzzy Theory and Intelligent Informatics
Medical Image Segmentation Techniques
article

Development of a Transfer Learning-Based Interactive Tool for Pathological Image Tissue Segmentation

Takeshi Terazawa, Toshiya Arakawa, Hoshiro SATO
article en

Abstract

No abstract available for this paper.
Journal of Japan Society for Fuzzy Theory and Intelligent InformaticsVol. 38(1)
Asahikawa Medical University (JP), Tokyo Denki University (JP), Advanced Engineering (Czechia) (CZ), Nippon Institute of Technology (JP)
Openalex Percentile: Top 56%
Medical Image Segmentation Techniques
DOIOpen Access PDFOpenAlex
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.