Deep Learning-Based Computer-Aided Detection System for Automated Treatment Response Assessment of Brain Metastases on 3D MRI
BackgroundAlthough accurate treatment response assessment for brain metastases (BMs) is crucial, it is highly labor intensive. This retrospective study aimed to develop a computer-aided detection (CAD) system for automated BM detection and treatment response evaluation using deep learning.MethodsWe...
Main Authors: | Jungheum Cho, Young Jae Kim, Leonard Sunwoo, Gi Pyo Lee, Toan Quang Nguyen, Se Jin Cho, Sung Hyun Baik, Yun Jung Bae, Byung Se Choi, Cheolkyu Jung, Chul-Ho Sohn, Jung-Ho Han, Chae-Yong Kim, Kwang Gi Kim, Jae Hyoung Kim |
---|---|
Format: | Article |
Language: | English |
Published: |
Frontiers Media S.A.
2021-10-01
|
Series: | Frontiers in Oncology |
Subjects: | |
Online Access: | https://www.frontiersin.org/articles/10.3389/fonc.2021.739639/full |
Similar Items
-
Response Assessment in Brain Metastases Managed by Stereotactic Radiosurgery: A Reappraisal of the RANO-BM Criteria
by: Keiss Douri, et al.
Published: (2023-10-01) -
MRI Texture Analysis for the Prediction of Stereotactic Radiosurgery Outcomes in Brain Metastases from Lung Cancer
by: Jung Hyun Park, et al.
Published: (2021-01-01) -
Editorial: Radiotherapy strategies for precise treatment on brain metastases
by: Eric J. Lehrer, et al.
Published: (2024-03-01) -
Management Strategies for Large Brain Metastases
by: Nehaw Sarmey, et al.
Published: (2022-02-01) -
Brain Metastases from Colorectal Cancer: A Systematic Review of the Literature and Meta-Analysis to Establish a Guideline for Daily Treatment
by: Sophie Müller, et al.
Published: (2021-02-01)