Parametric imaging in salivary gland scintigraphy

参数统计 人工智能 感兴趣区域 计算机科学 像素 减法 工件(错误) 分割 计算机视觉 可视化 图像分割 背景减法 模式识别(心理学) 数学 统计 算术
作者
Rogério Anton Faria,Graziella Chagas Jaguar,Eduardo Nóbrega Pereira Lima
出处
期刊:Nuclear Medicine Communications [Lippincott Williams & Wilkins]
标识
DOI:10.1097/mnm.0000000000001901
摘要

Salivary gland scintigraphy (SGS) is an imaging technique to evaluate functional aspects of the salivary glands. First described in 1965, visual analyses of summed images and of time–activity curves generated through regions of interest (ROI) are still the main evaluation tools used in clinical practice. An alternative to ROI-based analysis is the use of parametric images, which are images generated through pixel-by-pixel calculation of parameters from the original frames. In this article, we would like to present some parametric images for SGS studies and how to create and use them. Two images, vascular flow and uptake velocity, were created using the intercept and slope of a linear model of the frames from after the first to fifth minute of acquisition. And two others, excretion fraction and absolute excretion, by subtraction and division methods of the frames before and after sialogogue stimulation. These images allow the visualization of the spatial distribution and heterogeneity of these quantitative parameters, favoring different forms of analysis and helping with image segmentation. After more than a year of using these images in daily routine, our general impression is that they have been very helpful. This article, however, still represents only our early experiences with this technique, and clinical studies are yet needed to better evaluate this method.

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
刚刚
1秒前
1秒前
1秒前
平淡的万言应助你好呀采纳,获得10
2秒前
顾矜应助你好呀采纳,获得10
2秒前
爱听歌的树叶完成签到,获得积分10
2秒前
情怀应助qiu采纳,获得10
3秒前
尖叫尖叫发布了新的文献求助10
3秒前
卡夫卡cuf完成签到,获得积分10
4秒前
SciGPT应助s1采纳,获得10
5秒前
disjustar完成签到,获得积分0
5秒前
wanci应助大福麻薯采纳,获得10
5秒前
小雒雒发布了新的文献求助10
6秒前
7秒前
不吃茄子完成签到 ,获得积分10
9秒前
molihuakai应助s1采纳,获得10
10秒前
11秒前
12秒前
17秒前
淡然新竹发布了新的文献求助10
18秒前
Hello应助无心的成风采纳,获得10
19秒前
apricity完成签到,获得积分10
20秒前
还好发布了新的文献求助10
20秒前
21秒前
23秒前
ansteel应助Lqiang采纳,获得10
24秒前
26秒前
小蘑菇应助zhuhan采纳,获得10
26秒前
orixero应助QINXIANZI采纳,获得10
26秒前
bb完成签到 ,获得积分10
26秒前
27秒前
粗犷的路灯完成签到,获得积分10
27秒前
28秒前
打打应助深情的凝云采纳,获得10
28秒前
大福麻薯发布了新的文献求助10
30秒前
小蘑菇应助闪亮的屁灯采纳,获得10
30秒前
淡然新竹完成签到,获得积分20
30秒前
柒辞完成签到,获得积分10
32秒前
周八应助xzf1996采纳,获得10
33秒前
高分求助中
(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
Römisch-Germanische Forschungen 1000
APA handbook of comparative psychology: Basic concepts, methods, neural substrate, and behavior 1000
China Pluperfect I: Epistemology of Past and Outside in Chinese Art 520
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
The fast track to determining transfer functions of linear circuits: The student guide 500
The Analytical and Numerical Solution of Electric and Magnetic Fields 500
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 7610277
求助须知:如何正确求助?哪些是违规求助? 9186003
关于积分的说明 19678549
捐赠科研通 7184002
什么是DOI,文献DOI怎么找? 3270360
关于科研通互助平台的介绍 2434021
邀请新用户注册赠送积分活动 2265047