Visual Analytics for Hypothesis-Driven Exploration in Computational Pathology

Recent advances in computational and algorithmic power are evolving the field of medical imaging rapidly. In cancer research, many new directions are sought to characterize patients with additional imaging features derived from radiology and pathology images. The emerging field of Computational Path...

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Veröffentlicht in:	IEEE transactions on visualization and computer graphics 2021-10, Vol.27 (10), p.3851-3866
Hauptverfasser:	Corvo, A., Caballero, H. S. Garcia, Westenberg, M. A., van Driel, M. A., van Wijk, J. J.
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Biomarkers Biomedical imaging breast cancer Breast Neoplasms - diagnostic imaging Breast Neoplasms - genetics Breast Neoplasms - mortality Breast Neoplasms - pathology Cancer computational pathology Decision analysis Digital imaging Feature extraction Female Histological Techniques Humans Hypotheses hypothesis-driven exploration Image Interpretation, Computer-Assisted - methods Imaging Genomics - methods Machine Learning Medical imaging Medical research Pathology Radiography Spatial analysis Spatial distribution Tumors Visual analytics
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