Artificial Intelligence-based Tumor Segmentation in Mouse Models of Lung Adenocarcinoma
Background: Mouse models are highly effective for studying the pathophysiology of lung adenocarcinoma and evaluating new treatment strategies. Treatment efficacy is primarily determined by the total tumor burden measured on excised tumor specimens. The measurement process is time-consuming and prone...
Saved in:
Main Authors: | Alena Arlova (Author), Chengcheng Jin (Author), Abigail Wong-Rolle (Author), Eric S. Chen (Author), Curtis Lisle (Author), G. Thomas Brown (Author), Nathan Lay (Author), Peter L. Choyke (Author), Baris Turkbey (Author), Stephanie Harmon (Author), Chen Zhao (Author) |
---|---|
Format: | Book |
Published: |
Elsevier,
2022-01-01T00:00:00Z.
|
Subjects: | |
Online Access: | Connect to this object online. |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
The first step of artificial intelligence in dental practice: Segmentation applications
by: Elif ŞENER, et al.
Published: (2023) -
Artificial Intelligence in Medical Image Processing and Segmentation
Published: (2023) -
Artificial Intelligence for anatomical segmentation and use cases in CBCTs
by: Dr Thomas Choi
Published: (2023) -
Accurate gingival segmentation from 3D images with artificial intelligence: an animal pilot study
by: Min Yang, et al.
Published: (2023) -
Segmentation of periapical lesions with automatic deep learning on panoramic radiographs: an artificial intelligence study
by: Mehmet Boztuna, et al.
Published: (2024)