YOLO-TumorNet: An innovative model for enhancing brain tumor detection performance
Brain tumors are high-risk conditions where early detection and precise localization are crucial for improving patient prognosis. However, existing automated detection methods still exhibit limitations in robustness within complex backgrounds, boundary recognition, and the detection of small tumors,...
Saved in:
Main Authors: | Jian Huang, Wen Ding, Tiancheng Zhong, Gang Yu |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2025-04-01
|
Series: | Alexandria Engineering Journal |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S1110016825000894 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Brain tumor segmentation by deep learning transfer methods using MRI images
by: E.Y. Shchetinin
Published: (2024-06-01) -
Using Convolutional Neural Networks for segmentation of brain tumors
by: Kauã Gabriel Silva de Lima, et al.
Published: (2024-12-01) -
Clinical confocal laser endomicroscopy for imaging of autofluorescence signals of human brain tumors and non-tumor brain
by: Marlen Reichenbach, et al.
Published: (2024-12-01) -
CYBER SECURITY ANALYSIS OF IOT DEVICES TRANSMITTING DATA IN THE THINGSPEAK PLATFORM CLOUD
by: DRAGOS-ALEXANDRU ANDRIOAIA
Published: (2022-10-01) -
Hydrogel-based nanoparticles: revolutionizing brain tumor treatment and paving the way for future innovations
by: Alireza Shadab, et al.
Published: (2025-02-01)