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).
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