首页> Technology and health care : official journal of the European Society for Engineering and Medicine> Advancing brain tumor detection and classification in Low-Dose CT images using the innovative multi-layered deep neural network model.

Advancing brain tumor detection and classification in Low-Dose CT images using the innovative multi-layered deep neural network model.

导出 LinkOut

翻译打印收藏纠错

第一作者： Katari,Balakrishna

第一单位： Research Scholar, School of Computer Science and Engineering, VIT, Vellore, Tamil Nadu, India.

作者： Katari,Balakrishna ^[1] ; A Nagaraja,Rao ^[2]

作者单位： Research Scholar, School of Computer Science and Engineering, VIT, Vellore, Tamil Nadu, India. ^[1] Associate Professor, School of Computer Science and Engineering, VIT, Vellore, Tamil Nadu, India. ^[2]

关键词 Adaptive Histogram Equalisation Convolutional Neural Network Low Dose CT images Lucy-Richardson deconvolution complexity feature extraction feature extraction point-spread function

医学主题词人类(Humans);脑肿瘤(Brain Neoplasms);体层摄影术, X线计算机(Tomography, X-Ray Computed);图像处理, 计算机辅助(Image Processing, Computer-Assisted);辐射剂量(Radiation Dosage)

DOI 10.1177/09287329241302558

PMID 40331540

发布时间 2025-05-07

翻译满意度评价：

准确一般字义偏差语意偏离译文作用小提交

浏览1

Technology and health care

2025年33卷3期

1199-1220页

相似文献

中文期刊
外文期刊
学位论文
会议论文

浏览1

Technology and health care

2025年33卷3期

1199-1220页

检索历史清除

Advancing brain tumor detection and classification in Low-Dose CT images using the innovative multi-layered deep neural network model.

Technology and health care

相似文献

同项目论文

Technology and health care

相关期刊

参考文献：
指定格式：	NoteExpress EndNote RefWorks NoteFirst

检索历史 清除

Advancing brain tumor detection and classification in Low-Dose CT images using the innovative multi-layered deep neural network model.

Technology and health care

相似文献

同项目论文

Technology and health care

相关期刊

检索历史清除