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An automated wide-view imaging system of pathological tissue under optical microscopy

机译:光学显微镜下病理组织的自动宽视角成像系统

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Optical microscopy imaging techniques have been found widespread applications in medicine because of its capability of identifying anatomic features of pathological tissue. For the purpose of diagnostic, the image should be obtained in a form of wide-view with ultra-high resolution which provide quantitative information about the tissue. However, due to the limitation of acquired pixel size and field of view in imaging camera, an overview of biological specimens may not be acquired directly using current devices. In this contribution, an automated imaging system of wide-view of optical microscopy of pathological tissue was presented. Our research also involves seeking the fast stitching algorithm to form a panorama of the whole pathological tissue. Digital pathological images were obtained using our new microscope system and these images were scanned in blocks. During image acquisition, overlapping regions were appeared between neighboring block images to avoid missing border details. The whole images acquired were then reconstructed as a panorama of the whole sample with our improved fast stitching methods. The feasibility and performance of our proposed method was compared with classical methods and modern keypoint detectors to validated in processing clinical pathological images and proved to be high efficient and accurate.
机译:由于光学显微镜成像技术能够识别病理组织的解剖特征,因此已在医学中得到广泛应用。为了进行诊断,应以具有超高分辨率的宽视角形式获得图像,以提供有关组织的定量信息。然而,由于在成像照相机中所获取的像素大小和视野的限制,可能无法使用当前设备直接获取生物样本的概况。在这项贡献中,提出了一种病理组织光学显微镜的自动成像系统。我们的研究还涉及寻找快速缝合算法以形成整个病理组织的全景图。使用我们的新显微镜系统获得数字病理图像,并将这些图像分块扫描。在图像采集过程中,相邻块图像之间会出现重叠区域,以避免丢失边框细节。然后,使用我们改进的快速拼接方法,将获取的整个图像重建为整个样本的全景图。将我们提出的方法的可行性和性能与经典方法和现代关键点检测器进行了比较,以验证其在临床病理图像处理中的有效性和准确性。

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