Abstract
In this proposed study, SegNet is used for segmentation of cellular structures in high-resolution histopathological images. SegNet is a deep convolutional encoder-decoder architecture used for segmenting objects on the road and indoors. In this proposed study, the segmentation performance of SegNet algorithm for cellular structures in high resolution histopathological images is tried to be obtained. We also compared the performance of the SegNet algorithm with the state-of-the-art segmentation algorithms in the literature. According to the obtained results, SegNet has been observed to be quite successful compared to other methods commonly used in the segmentation of cellular structures.
Keywords
Segmentation
Encoder
Artificial intelligence
Computer science
Deep learning
Convolutional neural network
Image segmentation
Pattern recognition (psychology)
Computer vision
Algorithm
Scale-space segmentation
Subject Areas
AI in cancer detection
·Artificial Intelligence ·Physical Sciences
Digital Imaging for Blood Diseases
·Computer Vision and Pattern Recognition ·Physical Sciences
Cell Image Analysis Techniques
·Biophysics ·Life Sciences
Citations by Year
2019: 1
2021: 1
OpenAlex SDG Match
SDGs auto-classified by OpenAlex (score ≥ 0.4 shown).
Sustainable cities and communities 80%
Loading…
Loading…