Artifact Augmentation for Enhanced Tissue Detection in Microscope Scanner Systems
As the field of routine pathology transitions into the digital realm, there is a surging demand for the full automation of microscope scanners, aiming to expedite the process of digitizing tissue samples, and consequently, enhancing the efficiency of case diagnoses. The key to achieving seamless aut...
Main Authors: | Dániel Küttel, László Kovács, Ákos Szölgyén, Róbert Paulik, Viktor Jónás, Miklós Kozlovszky, Béla Molnár |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2023-11-01
|
Series: | Sensors |
Subjects: | |
Online Access: | https://www.mdpi.com/1424-8220/23/22/9243 |
Similar Items
-
Breast Ultrasound Images Augmentation and Segmentation Using GAN with Identity Block and Modified U-Net 3+
by: Meshrif Alruily, et al.
Published: (2023-10-01) -
Augmented Transformer network for MRI brain tumor segmentation
by: Muqing Zhang, et al.
Published: (2024-01-01) -
Enhanced Deep-Learning-Based Automatic Left-Femur Segmentation Scheme with Attribute Augmentation
by: Kamonchat Apivanichkul, et al.
Published: (2023-06-01) -
Advancing Barrett’s Esophagus Segmentation: A Deep-Learning Ensemble Approach with Data Augmentation and Model Collaboration
by: Jiann-Der Lee, et al.
Published: (2024-01-01) -
A two-stage U-net approach to brain tumor segmentation from multi-spectral MRI records
by: Győrfi Ágnes, et al.
Published: (2022-12-01)