HyMaP: A hybrid magnitude-phase approach to unsupervised segmentation of tumor areas in breast cancer histology images
Background: Segmentation of areas containing tumor cells in standard H&E histopathology images of breast (and several other tissues) is a key task for computer-assisted assessment and grading of histopathology slides. Good segmentation of tumor regions is also vital for automated scoring of immu...
Saved in:
Main Authors: | Adnan M Khan (Author), Hesham El-Daly (Author), Emma Simmons (Author), Nasir M Rajpoot (Author) |
---|---|
Format: | Book |
Published: |
Elsevier,
2013-01-01T00:00:00Z.
|
Subjects: | |
Online Access: | Connect to this object online. |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A gamma-gaussian mixture model for detection of mitotic cells in breast cancer histopathology images
by: Adnan Mujahid Khan, et al.
Published: (2013) -
Triple Hybrid (TriHy): What Happened When COVID Hit the Research Study
by: Ildiko Porter-Szucs, et al.
Published: (2024) -
Hypolipidemic and antioxidative effects of Curcumin on blood parameters, humoral immunity, and jejunum histology in Hy-line hens
by: Javad Arshami, et al.
Published: (2013) -
Unsupervised many-to-many stain translation for histological image augmentation to improve classification accuracy
by: Maryam Berijanian, et al.
Published: (2023) -
Unlocking high-value football fans: unsupervised machine learning for customer segmentation and lifetime value
by: Karim Chouaten, et al.
Published: (2024)