Guided interactive image segmentation using machine learning and color-based image set clustering.

ABSTRACT:

Motivation

Over the last decades, image processing and analysis has become one of the key technologies in systems biology and medicine. The quantification of anatomical structures and dynamic processes in living systems is essential for understanding the complex underlying mechanisms and allows, i.a., the construction of spatio-temporal models that illuminate the interplay between architecture and function. Recently, deep learning significantly improved the performance of traditional image analysis in cases where imaging techniques provide large amounts of data. However, if only few images are available or qualified annotations are expensive to produce, the applicability of deep learning is still limited.

Results

We present a novel approach that combines machine learning bas

SUBMITTER: Friebel A 

PROVIDER: S-EPMC9525009 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature