Teeth U-Net: A segmentation model of dental panoramic X-ray images for context semantics and contrast enhancement

计算机科学 语义学(计算机科学) 分割 人工智能 背景(考古学) 计算机视觉 对比度增强 网(多面体) 对比度(视觉) 计算机图形学(图像) 数学 医学 程序设计语言 放射科 地理 磁共振成像 考古 几何学
作者
Senbao Hou,Tao Zhou,Yuncan Liu,Pei Dang,Huiling Lu,Hongbin Shi
出处
期刊:Computers in Biology and Medicine [Elsevier BV]
卷期号:152: 106296-106296 被引量:53
标识
DOI:10.1016/j.compbiomed.2022.106296
摘要

It is very significant in orthodontics and restorative dentistry that the teeth are segmented from dental panoramic X-ray images. Nevertheless, there are some problems in panoramic X-ray images of teeth, such as blurred interdental boundaries, low contrast between teeth and alveolar bone.In this paper, The Teeth U-Net model is proposed in this paper to resolve these problems. This paper makes the following contributions: Firstly, a Squeeze-Excitation Module is utilized in the encoder and the decoder. And proposing a dense skip connection between encoder and decoder to reduce the semantic gap. Secondly, due to the irregular shape of the teeth and the low contrast of the dental panoramic X-ray images. A Multi-scale Aggregation attention Block (MAB) in the bottleneck layer is designed to resolve this problem, which can effectively extract teeth shape features and fuse multi-scale features adaptively. Thirdly, in order to capture dental feature information in a larger field of perception, this paper designs a Dilated Hybrid self-Attentive Block (DHAB) at the bottleneck layer. This module effectively suppresses the task-irrelevant background region information without increasing the network parameters. Finally, the effectiveness of the algorithm is validated using a clinical dental panoramic X-ray image datasets.The results of the three comparison experiments are shown that Accuracy, Precision, Recall, Dice, Volumetric Overlap Error and Relative Volume Difference for dental panoramic X-ray teeth segmentation are 98.53%, 95.62%, 94.51%, 94.28%, 88.92% and 95.97% by the proposed model respectively.The proposed modules complement each other in processing every detail of the dental panoramic X-ray images, which can effectively improve the efficiency of preoperative preparation and postoperative evaluation, and promote the application of dental panoramic X-ray in medical image segmentation. There are more accuracy about Teeth U-Net than others model in dental panoramic X-ray teeth segmentation. That is very important to clinical doctors to cure in orthodontics and restorative dentistry.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
花开富贵发布了新的文献求助10
刚刚
那个村的高手完成签到,获得积分10
刚刚
小马甲应助祺屿梦采纳,获得10
刚刚
青青草完成签到,获得积分10
1秒前
不安的小鸽子完成签到,获得积分10
1秒前
薇子完成签到,获得积分10
1秒前
2秒前
2秒前
zzh完成签到 ,获得积分10
3秒前
4秒前
拿铁小笼包完成签到,获得积分10
4秒前
小美美完成签到,获得积分10
6秒前
6秒前
6秒前
研友_VZG7GZ应助花开富贵采纳,获得10
7秒前
8秒前
8秒前
深情安青应助瞬间de回眸采纳,获得10
8秒前
白衣修身完成签到,获得积分10
8秒前
9秒前
酷炫橘子完成签到,获得积分10
9秒前
wu完成签到,获得积分10
9秒前
潘潘完成签到 ,获得积分10
9秒前
Elias完成签到 ,获得积分10
9秒前
Amber完成签到,获得积分10
10秒前
航某人完成签到,获得积分10
10秒前
研友_n0kjPL完成签到,获得积分0
11秒前
暴走小面包完成签到 ,获得积分10
11秒前
11秒前
闪闪靖荷完成签到,获得积分10
12秒前
顺其自然_666888完成签到,获得积分10
12秒前
奇思妙想十一吖完成签到 ,获得积分10
13秒前
Bismarck完成签到 ,获得积分10
13秒前
天边不羁云完成签到,获得积分10
13秒前
哈哈2022完成签到,获得积分10
13秒前
糟糕的雁菱完成签到 ,获得积分10
14秒前
科研欣路完成签到 ,获得积分10
14秒前
momo完成签到 ,获得积分10
14秒前
谯殿艺发布了新的文献求助10
14秒前
14秒前
高分求助中
Principles of Economics, 11th Edition 10000
University Physics with Modern Physics, 16th edition 10000
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Arthritis and Related Conditions, An Issue of Orthopedic Clinics 1000
Development of a Bridge Weigh-In-Motion System: A technology to convert the bridge response to the passage of traffic into data on vehicle configurations, speeds, times of travel and weights 1000
ズームレンズの光学設計に関する研究 800
Fundamentals of Pharmaceutical and Biologics Regulations: A Global Perspective, Second Edition 700
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7291011
求助须知:如何正确求助?哪些是违规求助? 8910016
关于积分的说明 18858473
捐赠科研通 6958420
什么是DOI,文献DOI怎么找? 3209203
关于科研通互助平台的介绍 2378998
邀请新用户注册赠送积分活动 2184974