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首页> 外文期刊>Computerized Medical Imaging and Graphics: The Official Jounal of the Computerized Medical Imaging Society >Determining histology-MRI slice correspondences for defining MRI-based disease signatures of prostate cancer.
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Determining histology-MRI slice correspondences for defining MRI-based disease signatures of prostate cancer.

机译:确定组织学-MRI切片对应关系,以定义前列腺癌基于MRI的疾病特征。

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Mapping the spatial disease extent in a certain anatomical organ/tissue from histology images to radiological images is important in defining the disease signature in the radiological images. One such scenario is in the context of men with prostate cancer who have had pre-operative magnetic resonance imaging (MRI) before radical prostatectomy. For these cases, the prostate cancer extent from ex vivo whole-mount histology is to be mapped to in vivo MRI. The need for determining radiology-image-based disease signatures is important for (a) training radiologist residents and (b) for constructing an MRI-based computer aided diagnosis (CAD) system for disease detection in vivo. However, a prerequisite for this data mapping is the determination of slice correspondences (i.e. indices of each pair of corresponding image slices) between histological and magnetic resonance images. The explicit determination of such slice correspondences is especially indispensable when an accurate 3D reconstruction of the histological volume cannot be achieved because of (a) the limited tissue slices with unknown inter-slice spacing, and (b) obvious histological image artifacts (tissue loss or distortion). In the clinic practice, the histology-MRI slice correspondences are often determined visually by experienced radiologists and pathologists working in unison, but this procedure is laborious and time-consuming. We present an iterative method to automatically determine slice correspondence between images from histology and MRI via a group-wise comparison scheme, followed by 2D and 3D registration. The image slice correspondences obtained using our method were compared with the ground truth correspondences determined via consensus of multiple experts over a total of 23 patient studies. In most instances, the results of our method were very close to the results obtained via visual inspection by these experts.
机译:将特定解剖器官/组织中的空间疾病程度从组织学图像映射到放射学图像对于定义放射学图像中的疾病特征很重要。一种这样的情况是在前列腺癌根治性前列腺切除术之前接受过术前磁共振成像(MRI)的男性前列腺癌患者中。对于这些情况,将来自离体全量组织学的前列腺癌范围映射到体内MRI。确定基于放射图像的疾病特征对于(a)培训放射科医生居民和(b)构建用于体内疾病检测的基于MRI的计算机辅助诊断(CAD)系统非常重要。然而,该数据映射的前提是确定组织学图像和磁共振图像之间的切片对应性(即,每对对应的图像切片对的索引)。当由于(a)切片间间距未知的有限组织切片,以及(b)明显的组织学图像伪影(组织丢失或组织缺损)而无法获得组织学体积的精确3D重建时,明确确定此类切片对应关系尤其必要。失真)。在临床实践中,组织学-MRI切片对应关系通常是由经验丰富的放射科医生和病理学家一致地目视确定的,但是此过程既费力又费时。我们提出了一种迭代方法,可通过逐组比较方案自动确定组织学和MRI图像之间的切片对应关系,然后进行2D和3D配准。在总共23个患者研究中,将使用我们的方法获得的图像切片对应关系与通过多个专家的共识确定的地面真实对应关系进行了比较。在大多数情况下,我们方法的结果与这些专家通过目视检查获得的结果非常接近。

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