Computer extracted nuclear features from Feulgen and H&amp;E images to predict biochemical recurrence in prostate cancer patients following radical prostatectomy.

Gawlik, Anna; Lee, George; Epstein, Jonathan I.; Veltri, Robert W.; Zhu, Guangjing; Pienta, Kenneth J.; Madabhushi, Anant

doi:10.1200/jco.2016.34.15_suppl.5067

Cited by 1 publication

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“…Research (157) has shown that the combination of nuclear architecture features from H&E- and Feulgen-stained images enabled prediction of BCR in prostate cancer patients; the combination of Feulgen and H&E resulted in better prognosis prediction than did H&E- or Feulgen-derived measurements alone. The results of this study are shown in Figure 8.…”

Section: Multimodal Digital Pathologymentioning

confidence: 99%

Emerging Themes in Image Informatics and Molecular Analysis for Digital Pathology

Bhargava

Madabhushi

2016

Annu. Rev. Biomed. Eng.

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125

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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.

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Section: Multimodal Digital Pathologymentioning

confidence: 99%