A Review of Caveats in Statistical Nuclear Image Analysis
A large body of the published literature in nuclear image analysis do not evaluate their findings on an independent data set. Hence, if several features are evaluated on a limited data set over‐optimistic results are easily achieved. In order to find features that separate different outcome classes...
Main Authors: | Helene Schulerud, Gunner B. Kristensen, Knut Liestøl, Liljana Vlatkovic, Albrecht Reith, Fritz Albregtsen, Hàvard E. Danielsen |
---|---|
Format: | Article |
Language: | English |
Published: |
Hindawi Limited
1998-01-01
|
Series: | Analytical Cellular Pathology |
Online Access: | http://dx.doi.org/10.1155/1998/436382 |
Similar Items
-
Prognostic Value of the Diversity of Nuclear Chromatin Compartments in Gynaecological Carcinomas
by: Andreas Kleppe, et al.
Published: (2020-12-01) -
The Use of Fractal Features from the Periphery of Cell Nuclei as a Classification Tool
by: Birgitte Nielsen, et al.
Published: (1999-01-01) -
The Prognostic Value of Adaptive Nuclear Texture Features from Patient Gray Level Entropy Matrices in Early Stage Ovarian Cancer
by: Birgitte Nielsen, et al.
Published: (2012-01-01) -
Prognostic Classification of Early Ovarian Cancer Based on very Low Dimensionality Adaptive Texture Feature Vectors from Cell Nuclei from Monolayers and Histological Sections
by: Birgitte Nielsen, et al.
Published: (2001-01-01) -
Caveats: Numerical Requirements in Graph Theory Based Quantitation of Tissue Architecture
by: J. Sudbø, et al.
Published: (2000-01-01)