Literature DB >> 15933077

Recent advances in observer performance methodology: jackknife free-response ROC (JAFROC).

Dev P Chakraborty1.   

Abstract

The jackknife free-response receiver operating characteristic (JAFROC) method allows quantitative analysis of observer data such as that observed when radiologists interpret images, which could contain more than one lesion and a location can be reported for each perceived lesion. The method was recently validated with a perception-based simulation model that incorporated the detectability parameter of the standard binormal ROC model, and in addition allowed simultaneous samples from both noise and signal distributions. The total number of noise samples is an important new parameter that measures reader expertise. The new sampling model incorporates search, which is an integral part of lesion detection that has not been possible to model until now. The model was used to generate simulated FROC ratings data, which was used to assess the statistical validity of JAFROC analysis. We found that JAFROC analysis is a statistically valid approach for analysing FROC data and that JAFROC analysis exhibited significantly greater statistical power than the existing ROC approach.

Mesh:

Year:  2005        PMID: 15933077     DOI: 10.1093/rpd/nch512

Source DB:  PubMed          Journal:  Radiat Prot Dosimetry        ISSN: 0144-8420            Impact factor:   0.972


  11 in total

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2.  Dose dependence of mass and microcalcification detection in digital mammography: free response human observer studies.

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Journal:  Med Phys       Date:  2007-02       Impact factor: 4.071

3.  Dose reduction and its influence on diagnostic accuracy and radiation risk in digital mammography: an observer performance study using an anthropomorphic breast phantom.

Authors:  T Svahn; B Hemdal; M Ruschin; D P Chakraborty; I Andersson; A Tingberg; S Mattsson
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4.  A Protease-Activated Fluorescent Probe Allows Rapid Visualization of Keratinocyte Carcinoma during Excision.

Authors:  Ethan Walker; Yiqiao Liu; InYoung Kim; David L Wilson; James P Basilion; Daniel L Popkin; Mark Biro; Sukanya Raj Iyer; Harib Ezaldein; Jeffrey Scott; Miesha Merati; Rachel Mistur; Bo Zhou; Brian Straight; Joshua J Yim; Matthew Bogyo; Margaret Mann
Journal:  Cancer Res       Date:  2020-03-04       Impact factor: 12.701

5.  Detection and diagnosis of colitis on computed tomography using deep convolutional neural networks.

Authors:  Jiamin Liu; David Wang; Le Lu; Zhuoshi Wei; Lauren Kim; Evrim B Turkbey; Berkman Sahiner; Nicholas A Petrick; Ronald M Summers
Journal:  Med Phys       Date:  2017-07-18       Impact factor: 4.071

6.  The diagnostic accuracy of dual-view digital mammography, single-view breast tomosynthesis and a dual-view combination of breast tomosynthesis and digital mammography in a free-response observer performance study.

Authors:  T Svahn; I Andersson; D Chakraborty; S Svensson; D Ikeda; D Förnvik; S Mattsson; A Tingberg; S Zackrisson
Journal:  Radiat Prot Dosimetry       Date:  2010-03-12       Impact factor: 0.972

7.  Magnetic resonance with diffusion-weighted imaging improves assessment of focal liver lesions in patients with potentially resectable pancreatic cancer on CT.

Authors:  Sun Kyung Jeon; Jeong Min Lee; Ijin Joo; Dong Ho Lee; Su Joa Ahn; Hyunsik Woo; Myoung Seok Lee; Jin-Young Jang; Joon Koo Han
Journal:  Eur Radiol       Date:  2018-01-19       Impact factor: 5.315

Review 8.  Model observers in medical imaging research.

Authors:  Xin He; Subok Park
Journal:  Theranostics       Date:  2013-10-04       Impact factor: 11.556

9.  One-view digital breast tomosynthesis as a stand-alone modality for breast cancer detection: do we need more?

Authors:  Alejandro Rodriguez-Ruiz; Albert Gubern-Merida; Mechli Imhof-Tas; Susanne Lardenoije; Alexander J T Wanders; Ingvar Andersson; Sophia Zackrisson; Kristina Lång; Magnus Dustler; Nico Karssemeijer; Ritse M Mann; Ioannis Sechopoulos
Journal:  Eur Radiol       Date:  2017-12-11       Impact factor: 5.315

Review 10.  The role of digital breast tomosynthesis in breast cancer screening: a manufacturer- and metrics-specific analysis.

Authors:  A Hadjipanteli; M Kontos; A Constantinidou
Journal:  Cancer Manag Res       Date:  2019-10-31       Impact factor: 3.989

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