Pathology is essential for research in disease and development, as well as for clinical decision making. For more than 100 years, pathology practice has involved analyzing images of stained, thin tissue sections by a trained human using an optical microscope. Technological advances are now driving major changes in this paradigm toward digital pathology (DP). The digital transformation of pathology goes beyond recording, archiving, and retrieving images, providing new computational tools to inform better decision making for precision medicine. First, we discuss some emerging innovations in both computational image analytics and imaging instrumentation in DP. Second, we discuss molecular contrast in pathology. Molecular DP has traditionally been an extension of pathology with molecularly specific dyes. Label-free, spectroscopic images are rapidly emerging as another important information source, and we describe the benefits and potential of this evolution. Third, we describe multimodal DP, which is enabled by computational algorithms and combines the best characteristics of structural and molecular pathology. Finally, we provide examples of application areas in telepathology, education, and precision medicine. We conclude by discussing challenges and emerging opportunities in this area.

中文翻译：

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图像信息学和数字病理学的分子分析中的新兴主题。

病理对于疾病和发展的研究以及临床决策至关重要。一百多年来，病理学实践涉及由训练有素的人使用光学显微镜分析染色的薄组织切片的图像。现在，技术进步正在推动这种模式向数字病理学（DP）的重大转变。病理学的数字化转换不仅限于记录，存档和检索图像，还提供了新的计算工具，可为精密医学提供更好的决策依据。首先，我们讨论DP中计算图像分析和成像仪器方面的一些新兴创新。其次，我们讨论了病理学中的分子对比。传统上，分子DP是分子特异性染料在病理学上的延伸。无标签，光谱图像正在迅速兴起，成为另一个重要的信息来源，我们描述了这种发展的好处和潜力。第三，我们描述了多峰DP，它由计算算法实现，并结合了结构和分子病理学的最佳特征。最后，我们提供了远程病理学，教育和精密医学领域的应用示例。最后，我们讨论该领域的挑战和新兴机会。