仿形(计算机编程)
计算机科学
可视化
人工智能
癌症
计算机视觉
钥匙(锁)
计算生物学
比例(比率)
三维重建
模式识别(心理学)
癌症检测
迭代重建
精密医学
生物
病理
特征(语言学)
医学影像学
素描
建筑
生物组织
癌症治疗
图像处理
作者
Ashley L. Kiemen,Laura D. Wood
标识
DOI:10.1146/annurev-cancerbio-070924-011950
摘要
Imaging biological samples in three dimensions across scales is essential for capturing the complex spatial relationships that govern cancer initiation, invasion, and therapeutic response. As biological inquiry shifts from isolated molecular measurements toward spatially contextualized, multiomic profiling, new strategies have emerged to reconstruct tissue architecture at the whole-organ scale and subcellular resolution. These advances offer more anatomically faithful representations of tissue organization and open doors to integrating morphology with deep multiomic profiling in spatially resolved formats. As a result, we are improving our understanding of inter- and intratumoral heterogeneity and the key role of rare events and minority cell populations in tumor progression. The primary techniques used for 3D imaging of tumors include intact tissue imaging for targeted visualization of biological processes and serial sectioning for integration of diverse, multiomic platforms. In this review, we survey the major technologies used to image tumors in three dimensions, highlighting key methodologies, trade-offs, and recent innovations that make these approaches increasingly central to modern cancer research.
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