OCT Daily Mar 18, 2017//Extended-focus optical coherence microscopy

Curated Paper

Optical coherence microscopy with extended focus for in vivo embryonic imaging

Abstract:

Optical coherence microscopy (OCM) has unique advantages of high-resolution volumetric imaging without relying on exogenous labels or dyes. It combines the coherence-gated depth discrimination of optical coherence tomography (OCT) with the high lateral resolution of confocal microscopy, offering an excellent balance between the resolutions and imaging depth. However, as the lateral resolution becomes higher, the imaging depth of OCM decreases and its three-dimensional imaging capability is greatly degraded. To overcome this limitation, we used amplitude apodization to create quasi-Bessel beam illumination in order to extend the depth of focus. The lateral and axial resolutions of our OCM system were measured to be 1.6 μm and 2.9 μm in tissue. The imaging depth was extended by 3.0X (100 μm) beyond that of the standard Gaussian beam OCM. Using zebrafish embryos as a test system, we demonstrate extendedfocus OCM for structural imaging studies, which revealed the detailed anatomy deep in embryos. © (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

Comments

首先,几个概念。

0.Gaussian 光束:

1.Bessel光束:

「无衍射光束」的概念是由美国Rochester大学的 J.Durnin 等人在1987年首次提出的,它是自由空间标量波动方程的一组特殊解,其场分布特点具有第一类零阶Bessel函数的表示形式。它以特殊的性质:在无界自由空间的传输过程中光强分布保持不变、中心光斑小、与传播方向垂直的各个平面上其光场分布保持相同,而且它的光强高度集中,也就是它的能量高度局域化,且不会在传播过程中遭受衍射扩散。

2.Fresnel菲涅尔透镜

相比传统的球面透镜,菲涅耳透镜通过将透镜划分出为一系列理论上无数多个同心圆纹路(即菲涅耳带)达到相同的光学效果,同时节省了材料的用量:

由于光的折射发生在介质的交界面,这里以玻璃与空气为例,若能去除光在玻璃中直线传播的部分而保留发生折射的曲面,便能省下大量材料同时达到相同的聚光效果。如图,菲涅耳透镜便是通过此法使透镜变薄。曲面划分得越细,透镜越能够做薄。

将普通透镜不参与折射的部分去掉,变成仅有参与折射的曲面的透镜。这个动画很有意思。菲涅尔透镜有一些列的环带组成,当平行光入射到菲涅尔透镜时,不同波长的光被聚焦到光轴上不同的点,实现光能量沿光轴的再分布。菲涅尔透镜的焦深是由波长所决定的焦点在光轴上所占的距离和单个波长的焦深之和,而波长所决定的焦点在光轴上所占的距离可以由最大波长的焦点与最小波长的焦点之间的确立来确定。

3.Axicon |AKSIKEN| 锥透镜

锥透镜通常也被称作轴对称棱镜,它是一种带一个圆锥面和一个平面的透镜。锥透镜常用来产生贝塞尔强度轮廓光束或者锥形非发散光束。当把准直光束转变为环形时,平的一面对着准直光源。

Based on above:

大多数OCT基本上是基于频域探测的谱域或者扫频光源OCT,研究全场OCT这样时域探测的很少。两者的区别在于,前者的探测是深度方向,而全场是面阵探测。本文在谱域探测的OCT中使用了全场OCT中惯用的显微物镜(跟我中国实验室一样的显微物镜),这样的使用无疑减小了焦深,焦深是什么详见这篇文章。为了维持深度方向的横向分辨率,主要原理:

  1. Bessel 光束代替 Gaussian 光束,然而由于有限能量和维数,通常是 Quasi-Bessel 光束
  2. 大多数采用轴锥棱镜,相位模板或者空间光调制器产生Quasi-Bessel 光束

但它们对宽带光源不友好(why?)(OCT使用宽带光源可得到高轴向分辨率该文章带宽为760-930 nm),故采用环状mask产生准Bessel光束来延长焦深,如图:

这篇文章的摘要说道:

To overcome this limitation, we used amplitude apodization(振幅变迹) to create quasi-Bessel beam illumination in order to extend the depth of focus.

从我的角度就是简单做了个圆环,模拟Bessel光束!

What can I learn from

1.这使我想起大师兄的博士论文的「基于菲涅尔透镜的SDOCT」:

横向分辨率与系统焦深之间的矛盾关系是目前SDOCT技术的一个热点问题。目前的SDOCT系统为了在横向分辨率和焦深之间达到一个平衡,一般在样品臂都使用低数值孔径的物镜,为了改善这一矛盾关系,通过对现有方法的大量分析与研究,在现有方法的基础上,提出了利用菲涅尔透镜替代普通物镜的方法,来改善这一问题。本章首先介绍了其它小组提出的改善这一矛盾关系的几种方法,接着介绍了基于菲涅尔透镜的SDOCT系统的原理,并用所搭建的系统对人体皮肤进行了在体成像,验证了系统的可行性,最后对色散问题进行了讨论。

基于菲涅尔透镜的SDOCT系统事实上是将传统SDOCT系统中的普通物镜换成菲涅尔透镜,利用菲涅尔透镜的一些性质实现焦深的增加。

2.和一篇新文章,使用 axicon lens 轴锥棱镜的SDOCT:

Extended focus depth for Fourier domain optical coherence microscopy

The Bessel beam was generated by the axicon lens and transferred to the object using a set of telescopes. The annular aperture was inserted in the first telescope to block unwanted residual rays coming from the imperfect axicon tip.

这篇新文章,使用锥透镜,还用圆环挡住不需要的残余光线。

3.和一篇新文章 Simultaneous dual-band ultra-high resolution full-field optical coherence tomography

The effective spectra are deduced from Fourier transform of the interferogram using a Hamming window for apodization

4.Bessel beam in FFOCT

5.可变焦棱镜(non scanning)Fast electrically tunable lens EL-10-30-TC

OCT Daily Mar 14, 2017, 08:15

Curated Paper

Integrated Local Binary Pattern Texture Features for Classification of Breast Tissue Imaged by Optical Coherence Microscopy

Abstract:

Highlights

• Texture analysis is applied on OCM images for human breast tissue classification.

• New variants of local binary pattern (LBP) are proposed to extract texture features.

• Using multi-scale and integrated image features improves classification accuracy.

• Achieved high sensitivity (100%) and specificity (85.2%) for cancer detection.

Comments

昨天的 OCT Daily Mar 13 写到了对乳腺癌成像结果分析以及初诊,今天这篇来自Fujimoto实验室,同样对乳腺癌进行纹理配对分析,值得注意的是在 Image Processing 部分,文章提到:

The images utilized in our experiments in this work are en face OCM images of ex vivo human breast tissue.

上图显示了邻域图案到量化的过程,下图是具体处理过程。

这里提及另一篇文章。因为FDOCT(大部分)是以一个A扫为单位的,也就是说必须使用振镜扫描才能得到所谓的 en face 结构。而这篇文献的主从模式干涉结构1

Conventional spectral domain interferometry (SDI) methods suffer from the need of data linearization. When applied to optical coherence tomography (OCT), conventional SDI methods are limited in their 3D capability, as they cannot deliver direct en-face cuts. Here we introduce a novel SDI method, which eliminates these disadvantages. We denote this method as Master – Slave Interferometry (MSI), because a signal is acquired by a slave interferometer for an optical path difference (OPD) value determined by a master interferometer. The MSI method radically changes the main building block of an SDI sensor and of a spectral domain OCT set-up. The serially provided signal in conventional technology is replaced by multiple signals, a signal for each OPD point in the object investigated. This opens novel avenues in parallel sensing and in parallelization of signal processing in 3D-OCT, with applications in high-resolution medical imaging and microscopy investigation of biosamples. Eliminating the need of linearization leads to lower cost OCT systems and opens potential avenues in increasing the speed of production of en-face OCT images in comparison with conventional SDI.

What can I learn from



全场OCT存在的必要性。医生诊断还是需要 en face image。全场OCT的缺点:

  1. 不稳定
  2. 灵敏度不如 FDOCT
  3. 成像深度浅 – 500$\mu m$

除此之外,也提供了识别癌症的一种思路。SensitivitySpecificity是判断癌症与否的两个指标。

  1. Bradu, A. & Podoleanu, A. G. Imaging the eye fundus with real-time en-face spectral domain optical coherence tomography. Biomed. Opt. Express 5, 1233-1249, doi:10.1364/BOE.5.001233 (2014).

OCT Daily Mar 13, 2017

这篇文章讲述了一个女性如何在自己的领域为乳腺癌的初诊做的事情。

Curated Paper

Visualization and tissue classification of human breast cancer images using ultrahigh-resolution OCT

Abstract:

Breast cancer is one of the leading cause of mortality in women. Optical coherence tomography (OCT) enables three dimensional visualization of biological tissue with micrometer level resolution at high speed, and can play an important role in early diagnosis and treatment guidance of breast cancer. In this study, we imaged human breast tissue using two spectral domain OCT systems at different wavelengths: a home-built ultra-high resolution (UHR) OCT system at 840nm (measured as 2.72 µm axial and 5.52 µm lateral) and a commercial OCT system at 1300nm with standard resolution (measured as 6.5 µm axial and 15 µm lateral). We found that detailed structures of basic units found in breast tissue, such as TDLUs, ducts, adipose and fibrous stroma, can be better delineated by UHR OCT. In addition, we added phyllodes, fibrotic focus and necrotic tumor to the UHR OCT image library of breast cancer. Moreover, by using regional features derived from OCT images produced by the two systems, we developed an automated classification algorithm based on relevance vector machine (RVM) to differentiate hollow-structured adipose tissue against solid tissue. We further developed B-scan based features for RVM to classify invasive ductal carcinoma (IDC) against normal fibrous stroma tissue amongst OCT datasets produced by the two systems. With a limited number of datasets, we showed that both OCT systems can achieve a good accuracy in identifying adipose tissue. Classification in UHR OCT images achieved higher sensitivity (94%) and specificity (93%) of adipose tissue than the sensitivity (91%) and specificity (76%) in 1300 nm OCT images. In IDC classification, similarly, we achieved better results with UHR OCT images, featured an overall accuracy of 84%, sensitivity of 89% and specificity of 71% in this preliminary study. Our work may open the door towards automatic intraoperative OCT evaluation of early-stage breast cancer.

Comments

Christine Hendon的实验室,虽然她当年压根没理我的信。Basic OCT scheme:

利用OCT对乳腺癌的成像和数据分析,Tissue classification algorithm flow/ 组织分类算法流程图如下:

定义灵敏度和确认度分析肿瘤结构,还跟Thorlabs OCT和传统病理学结果对比,部分成像结果如下:

诊断分类(阳性,阴性)分析对比结果如下:

In particular, ultra-high resolution (UHR) OCT provides images with better histological correlation.

What can I learn from

已经从对成像的改进进入到实用领域,像DeepMind这类公司利用Machine Learning 取代病理识别已经是趋势。该文章给我提供了一个流程,包括SBO LAB的文章1和FFOCT对乳腺癌的诊断2,试图解决这样一个问题:如何从成像结果变成可量化的结论。

具体为对图片有什么要求,比如:

All OCT images presented have a corresponding histology slides, which were annotated with the help of an experienced pathologist. The aspect ratio of UHR OCT images was scaled to match the dimension of the actual cross-sectional field of view in air (3 mm by 1.78 mm), and Thorlabs OCT images were presented in their original scale.

但目前如何以 Decent way 做组织病理学实验还需要专业病理科医生指导。

  1. Zarnescu, L. et al. Label-free characterization of vitrification-induced morphology changes in single-cell embryos with full-field optical coherence tomography. BIOMEDO 20, 096004-096004, doi:10.1117/1.JBO.20.9.096004 (2015).
  2. Assayag, O. et al. Large Field, High Resolution Full-Field Optical Coherence Tomography: A Pre-Clinical Study of Human Breast Tissue and Cancer Assessment. Technology in Cancer Research & Treatment 13, 455-468, doi:doi:10.7785/tcrtexpress.2013.600254 (2014).

OCT Daily Mar 10, 2017

Curated paper

Accurate wavelength calibration method for compact CCD spectrometer

Abstract:

Wavelength calibration is an important step in charge-coupled device (CCD) spectrometers. In this paper, an accurate calibration method is proposed. A model of a line profile spectrum is built at the beginning, followed by noise reduction, bandwidth correction, and automatic peak-seeking treatment. Experimental tests are conducted on the USB4000 spectrometer with a mercury-argon calibration light source. Compared with the traditional method, the results show that this wavelength calibration procedure obtains higher accuracy and the deviations are within 0.1 nm.

简评

这是一篇关于利用自动选择光谱OCT峰值信号,进行光谱标定的文章。没有太多新意,比较实用的算法文章。

内核分成三部分:

  1. 噪声分析与消噪算法
  2. 校正带宽
  3. 自动识别峰值信号

噪声(read out noise/dark noise/photoelectron noise/fixed pattern noise)消噪算法(平均算法,小波阈值算法)。

校正带宽用{Woolliams, 2011 #512}提出的差分算法1

自动识别峰值信号。方法一:将离散信号当作连续曲线,通过使用数值微分公式来计算每个点的导数。峰中心的位置是一阶导数的过零点的对应像素数。

What I can learn from

三种自动识别峰值的方法,目前我确实是手动选择,但仅仅一次就足够,如果自动识别,可能还是要筛选前后区域来重复。该文章仅仅提供一种可能性,

  1. Woolliams, E. R., Baribeau, R., Bialek, A. & Cox, M. G. Spectrometer bandwidth correction for generalized bandpass functions. Metrologia 48, 164 (2011).

OCT Daily Mar 9, 2017

Curated paper

Full-Field Optical Coherence Tomography as a Diagnosis Tool: Recent Progress with Multimodal Imaging

Abstract:

Full-field optical coherence tomography (FF-OCT) is a variant of OCT that is able to register 2D en face views of scattering samples at a given depth. Thanks to its superior resolution, it can quickly reveal information similar to histology without the need to physically section the sample. Sensitivity and specificity levels of diagnosis performed with FF-OCT are 80% to 95% of the equivalent histological diagnosis performances and could therefore benefit from improvement. Therefore, multimodal systems have been designed to increase the diagnostic performance of FF-OCT. In this paper, we will discuss which contrasts can be measured with such multimodal systems …

What I can learn from

This is my goal in the near future