In this paper, we present a distal-scanning common path probe for optical coherence tomography (OCT) equipped with a hollow ultrasonic motor and a simple and specially designed beam-splitter. This novel probe proves to be able to effectively circumvent polarization and dispersion mismatch caused by fiber motion and is more robust to a variety of interfering factors during the imaging process, experimentally compared to a conventional noncommon path probe. Furthermore, our design counteracts the attenuation of backscattering with depth and the fall-off of the signal, resulting in a more balanced signal range and greater imaging depth. Spectral-domain OCT imaging of phantom and biological tissue is also demonstrated with a sensitivity of ～100dB and a lateral resolution of ～3μm. This low-cost probe offers simplified system configuration and excellent robustness, and is therefore particularly suitable for clinical diagnosis as one-off medical apparatus.

Photoacoustic imaging (PAI) is a noninvasive emerging imaging method based on the photoacoustic effect, which provides necessary assistance for medical diagnosis. It has the characteristics of large imaging depth and high contrast. However, limited by the equipment cost and reconstruction time requirements, the existing PAI systems distributed with annular array transducers are difficult to take into account both the image quality and the imaging speed. In this paper, a triple-path feature transform network (TFT-Net) for ring-array photoacoustic tomography is proposed to enhance the imaging quality from limited-view and sparse measurement data. Specifically, the network combines the raw photoacoustic pressure signals and conventional linear reconstruction images as input data, and takes the photoacoustic physical model as a prior information to guide the reconstruction process. In addition, to enhance the ability of extracting signal features, the residual block and squeeze and excitation block are introduced into the TFT-Net. For further efficient reconstruction, the final output of photoacoustic signals uses ‘filter-then-upsample’ operation with a pixel-shuffle multiplexer and a max out module. Experiment results on simulated and in-vivo data demonstrate that the constructed TFT-Net can restore the target boundary clearly, reduce background noise, and realize fast and high-quality photoacoustic image reconstruction of limited view with sparse sampling.

Optical molecular tomography (OMT) is a potential pre-clinical molecular imaging technique with applications in a variety of biomedical areas, which can provide non-invasive quantitative three-dimensional (3D) information regarding tumor distribution in living animals. The construction of optical transmission models and the application of reconstruction algorithms in traditional model-based reconstruction processes have affected the reconstruction results, resulting in problems such as low accuracy, poor robustness, and long-time consumption. Here, a gates joint locally connected network (GLCN) method is proposed by establishing the mapping relationship between the inside source distribution and the photon density on surface directly, thus avoiding the extra time consumption caused by iteration and the reconstruction errors caused by model inaccuracy. Moreover, gates module was composed of the concatenation and multiplication operators of three different gates. It was embedded into the network aiming at remembering input surface photon density over a period and allowing the network to capture neurons connected to the true source selectively by controlling three different gates. To evaluate the performance of the proposed method, numerical simulations were conducted, whose results demonstrated good performance in terms of reconstruction positioning accuracy and robustness.

Limited by the dynamic range of the detector, saturation artifacts usually occur in optical coherence tomography (OCT) imaging for high scattering media. The available methods are difficult to remove saturation artifacts and restore texture completely in OCT images. We proposed a deep learning-based inpainting method of saturation artifacts in this paper. The generation mechanism of saturation artifacts was analyzed, and experimental and simulated datasets were built based on the mechanism. Enhanced super-resolution generative adversarial networks were trained by the clear–saturated phantom image pairs. The perfect reconstructed results of experimental zebrafish and thyroid OCT images proved its feasibility, strong generalization, and robustness.

脑胶质瘤是一种侵袭性的恶性原发性脑肿瘤，术中准确区分胶质瘤和正常脑组织极具挑战性。基于高分辨偏振敏感光学相干层析术（PS-OCT）对正常小鼠脑和胶质瘤模型小鼠脑进行成像，计算了强度、累积相位延迟和累积光轴信息。结果表明，从PS-OCT图像中可以清楚地显示出鼠脑中的纤维结构及其取向；借助PS-OCT图像中丰富的偏振信息，可以准确区分鼠脑胶质瘤区和正常区；基于计算的光轴标准差可以有效区分胶质瘤和正常脑组织。研究结果表明，高分辨PS-OCT在脑组织成像及脑胶质瘤识别方面具有很大的临床应用潜力。

动脉粥样硬化引起的易损斑块破裂已经严重危害到人类的健康，而血管内光学相干断层成像（IVOCT）凭借其高分辨率已经成为识别冠脉易损斑块的主要工具，但图像判读费时费力，通常还依赖于医生的经验。目前已有基于传统机器学习的研究实现了对单帧图像的分类，但这些信息不足以辅助医生确定治疗方案，仍然需要医生二次判读。基于Faster R-CNN（R-CNN，区域卷积神经网络），针对IVOCT图像中易损斑块的特点，在数据增强、预测框（BBox）编码、网络结构等方面进行了改进和优化，实现了对易损斑块的自动识别，并选取易损斑块的病变累积角度、纤维帽厚度、巨噬细胞浸润情况、浅表微钙化情况和血管狭窄程度作为指标，对易损斑块的破裂风险进行多方面评估。在公开数据集CCCV2017 IVOCT中进行训练，测试后取得了较好结果，该方法可推广应用于同类图像。

近红外光谱断层成像是一种可以获得乳腺组织内部光学特性，弥补传统乳腺影像学检查方法的不足，具有无创无辐射、高特异性等特性，在乳腺成像中有重要应用价值的光学成像技术。近红外光谱断层成像系统对该技术在乳腺疾病临床诊断中的应用起着重要的作用。然而，近红外光谱断层成像系统的空间分辨率低，限制了其在乳腺成像中的应用。将连续波模式与频域或时域测量模式相结合，并融合临床用的数字乳腺断层摄影、超声或核磁共振成像等技术有助于解决上述问题。先对近红外光谱断层成像系统的测量模式、多模态系统和多模态融合技术进行梳理、对比，然后介绍了该技术在乳腺成像中的最新应用，进一步讨论了乳腺近红外光谱断层成像系统未来的发展方向。

光学相干层析成像（OCT）是一种高空间分辨率的光学成像方法，可以对生物组织进行非接触、无标记的二维截面和三维体积成像，能为临床疾病的诊断提供具有重要参考价值的影像信息。在传统的台式OCT系统中，扫描探头被固定在工作台上，探头结构较大，灵活性差，不利于深入狭小腔体内部成像或在床旁检测。本团队设计了一种视频引导的手持式高速OCT系统，其手持探头结构紧凑、体积小巧，便于抓取和深入狭小腔体内部；探头内部集成了相机成像功能，可以实时获得成像区域的视频图像，引导OCT成像。该系统的A线扫描速率可以达到200 kHz。为了克服成像过程中的抖动问题，本团队提出了图像自动配准算法，该算法能显著提高图像质量。采用该系统对离体猪眼角膜和离体猪牙齿进行成像，以验证系统的性能。结果显示该系统能够高速获取高分辨的组织图像。

针对相对平行直线扫描CT（PTCT）图像重建存在的有限角伪影问题，提出一种学习局部和非局部正则项的深度迭代展开方法。该方法将具有固定迭代次数的梯度下降算法迭代展开到神经网络，利用具有坐标注意力（CA）机制的卷积模块和Swin-Transformer模块作为迭代模块交替级联部署，构成端到端的深度重建网络。卷积模块学习局部正则化，其中CA用于减少图像过平滑；Swin-Transformer模块学习非局部正则化，提高网络对图像细节的恢复能力；在相邻模块间，使用迭代连接（IC）增强模型提取深层特征的能力，提高每次迭代的效率。通过消融实验验证了网络各部分的有效性，并在两种类型的数据集上进行实验，结果证明了本文方法的效果。实验结果表明，本文方法在抑制PTCT重建图像有限角伪影的同时，能较好地保留重建图像细节，提高重建图像质量。