a= ['magnetic', 'resonance' ,'imaging']依次取出 imaging,resonance imaging

要依次取出 "imaging" 和 "resonance imaging"，可以使用以下代码：

a= ['magnetic', 'resonance' ,'imaging']
last_element = a.pop()  # 弹出最后一个元素 "imaging"
second_last_element = " ".join([a.pop(), last_element])  # 弹出 "resonance" 并与 "imaging" 拼接
print(last_element)  # 输出 "imaging"
print(second_last_element)  # 输出 "resonance imaging"

注意，这里使用了 `pop()` 方法弹出列表中的元素，因此原列表 `a` 中会缺少这些元素。如果不想修改原列表，可以先对 `a` 做一份拷贝，如 `a_copy = a.copy()`，然后对 `a_copy` 进行操作。

相关问题

magnetic resonance imaging——physical principles and sequence des

磁共振成像（MRI）是一种医学影像技术，使用强磁场和无害的无线电波来生成身体内部的详细图像。其工作原理基于基本的物理原理和一系列的脉冲序列。

MRI的物理原理主要涉及到原子的磁性和自旋概念。人体组织中的大部分原子都具有自旋，即自身带有角动量。在磁场中，原子的自旋会与磁场方向相同或相反地排列。当磁场发生改变时，原子的自旋也会发生改变。利用这种自旋特性，可以通过对原子进行刺激来生成可视化的图像。

MRI的序列设计是基于脉冲的概念。在脉冲序列中，通过特定的时间和能量设置，可控制原子的自旋状态。常见的MRI序列包括T1加权序列和T2加权序列。T1加权序列通过使组织中的水分子在外加磁场作用下的自旋状态恢复到平衡来生成图像，用于显示解剖结构。T2加权序列则通过使组织中的水分子的自旋状态相互之间的松弛时间延迟来生成图像，用于显示水分子在组织中的分布和性质。

在MRI扫描过程中，患者将被放置在一个强大的磁场中，通常是静止的或移动的。无线电波将被用来刺激患者体内的原子自旋，并通过检测其自旋响应来生成图像。生成的图像可以提供关于组织结构、病变和功能信息。

总结来说，MRI的物理原理涉及到原子的磁性和自旋概念，利用无线电波来刺激原子自旋并生成可视化的图像。脉冲序列的设计用于控制原子自旋状态和生成不同类型的图像。通过深入理解MRI的物理原理和序列设计，可以更好地应用和解读MRI图像，为医学诊断和研究提供帮助。

Voxel-based morphometric magnetic resonance imaging (MRI) postprocessing

Voxel-based morphometric magnetic resonance imaging (MRI) postprocessing is a technique used to analyze brain images obtained from MRI scans. It involves the use of computer software to measure and compare the volume, density, and shape of brain structures across individuals or groups.

The process starts with acquiring high-resolution MRI images of the brain, which are then processed using specialized software. The images are first aligned to a standardized brain template to ensure consistency across individuals. Then, the images are segmented into different brain regions based on their anatomical features.

Once the regions of interest have been identified, statistical analyses are performed to compare the volume, density, or shape of these regions between individuals or groups. This can reveal differences in brain structure that may be associated with certain neurological or psychiatric disorders.

Voxel-based morphometry (VBM) is a specific type of voxel-based morphometric MRI postprocessing that focuses on analyzing differences in brain tissue density. It is often used to study changes in gray and white matter in the brain associated with aging, disease, or injury.

Overall, voxel-based morphometric MRI postprocessing is a powerful tool for studying the structure and function of the brain, and it has important implications for understanding and treating neurological and psychiatric disorders.