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Statistical framework for validation without ground truth of choroidal thickness changes detection.
Ronchetti, Tiziano; Jud, Christoph; Maloca, Peter M; Orgül, Selim; Giger, Alina T; Meier, Christoph; Scholl, Hendrik P N; Chun, Rachel Ka Man; Liu, Quan; To, Chi-Ho; Povazay, Boris; Cattin, Philippe C.
Afiliación
  • Ronchetti T; Department of Biomedical Engineering (DBE), University of Basel, Basel, Switzerland.
  • Jud C; Institute for Human Centered Engineering (HuCE)-optoLab, Bern University of Applied Sciences, Bern, Switzerland.
  • Maloca PM; OCTlab, Department of Ophthalmology, University Hospital Basel, Basel, Switzerland.
  • Orgül S; Department of Biomedical Engineering (DBE), University of Basel, Basel, Switzerland.
  • Giger AT; OCTlab, Department of Ophthalmology, University Hospital Basel, Basel, Switzerland.
  • Meier C; Department of Ophthalmology, University of Basel, Basel, Switzerland.
  • Scholl HPN; Moorfields Eye Hospital, London, United Kingdom.
  • Chun RKM; Institute of Molecular and Clinical Ophthalmology Basel (IOB), Basel, Switzerland.
  • Liu Q; Department of Ophthalmology, University of Basel, Basel, Switzerland.
  • To CH; Department of Biomedical Engineering (DBE), University of Basel, Basel, Switzerland.
  • Povazay B; Institute for Human Centered Engineering (HuCE)-optoLab, Bern University of Applied Sciences, Bern, Switzerland.
  • Cattin PC; Department of Ophthalmology, University of Basel, Basel, Switzerland.
PLoS One ; 14(6): e0218776, 2019.
Article en En | MEDLINE | ID: mdl-31251762
Monitoring subtle choroidal thickness changes in the human eye delivers insight into the pathogenesis of various ocular diseases such as myopia and helps planning their treatment. However, a thorough evaluation of detection-performance is challenging as a ground truth for comparison is not available. Alternatively, an artificial ground truth can be generated by averaging the manual expert segmentations. This makes the ground truth very sensitive to ambiguities due to different interpretations by the experts. In order to circumvent this limitation, we present a novel validation approach that operates independently from a ground truth and is uniquely based on the common agreement between algorithm and experts. Utilizing an appropriate index, we compare the joint agreement of several raters with the algorithm and validate it against manual expert segmentation. To illustrate this, we conduct an observational study and evaluate the results obtained using our previously published registration-based method. In addition, we present an adapted state-of-the-art evaluation method, where a paired t-test is carried out after leaving out the results of one expert at the time. Automated and manual detection were performed on a dataset of 90 OCT 3D-volume stack pairs of healthy subjects between 8 and 18 years of age from Asian urban regions with a high prevalence of myopia.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Coroides / Imagenología Tridimensional / Tomografía de Coherencia Óptica Tipo de estudio: Diagnostic_studies / Guideline / Observational_studies / Risk_factors_studies Límite: Adolescent / Child / Female / Humans / Male Idioma: En Revista: PLoS One Asunto de la revista: CIENCIA / MEDICINA Año: 2019 Tipo del documento: Article País de afiliación: Suiza Pais de publicación: Estados Unidos
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Coroides / Imagenología Tridimensional / Tomografía de Coherencia Óptica Tipo de estudio: Diagnostic_studies / Guideline / Observational_studies / Risk_factors_studies Límite: Adolescent / Child / Female / Humans / Male Idioma: En Revista: PLoS One Asunto de la revista: CIENCIA / MEDICINA Año: 2019 Tipo del documento: Article País de afiliación: Suiza Pais de publicación: Estados Unidos