Title: Comparative effectiveness of standard versus AI-assisted PET/CT reading workflow for pre-treatment lymphoma staging – Multi-institutional reader study evaluation.

Frood R, Willaime JMY, Miles B, Chambers G, Al-Chalabi H, Ali T, Hougham N, Brooks N, Petrides G, Naylor M, Ward D, Sulkin T, Chaytor R, Strouhal P, Patel C, Scarsbrook A. Comparative effectiveness of standard versus AI-assisted PET/CT reading workflow for pre-treatment lymphoma staging – Multi-institutional reader study evaluation [Conference Presentation Abstract, M3-SSNMMI03-2]. RSNA 2022, Chicago, IL, United States.

 

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Title: Reporter confidence of an AI-assisted PET/CT reading workflow in pre treatment assessment of high-grade lymphoma : multi-centre reader study 

Frood R, Willaime JMY, Miles B, Brooks N, Strouhal P, Patel C, Scarsbrook A. Reporter confidence of an AI-assisted PET/CT reading workflow in pre-treatment assessment of high-grade lymphoma : multi-centre reader study [Poster Presentation]. ECR 2023, Vienna, Austria.

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Title : Impact of training dataset size on technical performance of a deep learning model for detection and quantification of lymphomatous disease on 18F-FDG PET/CT

 Ionescu GV, Frood R, Scarsbrook AF, Willaime JMY. Impact of training dataset size on technical performance of a deep learning model for detection and quantification of lymphomatous disease on 18F-FDG PET/CT study [Poster Presentation]. SNMMI 2023, Chicago, IL, United States. In: J Nucl Med 2023; 64 (Supplement 1): 1069. https://jnm.snmjournals.org/content/64/supplement_1/P1069

 

 

Title:  Non-Uniqueness of Multiexponential Time-Activity Curves

Balfour D, Sage J, Willaime JMY and Boukerroui D. Non-Uniqueness of Multiexponential Time-Activity Curves in Few-Timepoint Theranostic Workflows Can Increase Dosimetric Error [Conference Presentation, OP-907]. EANM 2023, Vienna, Austria. In: EANM’23 Abstract Book Congress, Eur J Nucl Med Mol Imaging 50 (Suppl 1), 1–898 (2023). https://doi.org/10.1007/s00259-023-06333-x

                                              

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Title:  Uncertainty analysis of AI-generated contours for molecular radiotherapy dosimetry

Looney P, McQuinlan Y, Sage J and Willaime JMY. Uncertainty analysis of AI-generated contours for molecular radiotherapy dosimetry [Poster Presentation]. The British Institute of Radiology AI in NM&PET meeting, 2023 October 9, Oxford, UK.

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Title: Investigation into the risk of population bias in deep learning autocontouring.

McQuinlan Y, Brouwer CL, Lin Z, Gan Y, Sung Kim J, van Elmpt W, Gooding M J. An investigation into the risk of population bias in deep learning autocontouring. Radiotherapy and Oncology 186, 109747.

 

Title: Analytic calculations and synthetic shapes for validation of quantitative contour comparison software.

Boukerroui D, Osorio EV, Brunenberg E, Gooding MJ. Analytic calculations and synthetic shapes for validation of quantitative contour comparison software. Physics and Imaging in Radiation Oncology 26, 100436. https://doi.org/10.1016/j.phro.2023.100436

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Title: Comparative effectiveness of standard versus AI-assisted PET/CT reading workflow for pre-treatment lymphoma staging – Multi-institutional reader study evaluation.

Frood R, Willaime JMY, Miles B, Chambers G, Al-Chalabi H, Ali T, Hougham N, Brooks N, Petrides G, Naylor M, Ward D, Sulkin T, Chaytor R, Strouhal P, Patel C, Scarsbrook A. Comparative effectiveness of standard versus AI-assisted PET/CT reading workflow for pre-treatment lymphoma staging – Multi-institutional reader study evaluation. Frontiers in Nuclear Medicine. 2024;3:1327186. https://doi.org/10.3389/fnume.2023.1327186

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Title: What level of AI explainability do radiologists need in Nuclear Medicine? A user-centred evaluation

Baskerville C, Wells K, Prakash V, Willaime J. What level of AI explainability do radiologists need in Nuclear Medicine? A user-centred evaluation [Oral Presentation, 65]. BNMS 2024 Spring Meeting, Belfast, Northern Ireland.

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Title: Automatic disease detection and segmentation on 18F-FDG PET/CT - Do Deep Learning models mirror clinical annotation style?

Ionescu G, Frood R, Scarsbrook A, Willaime J. Automatic disease detection and segmentation on 18F-FDG PET/CT - Do Deep Learning models mirror clinical annotation style? [Poster Presentation]. SNMMI 2024, Chicago, IL, United States. In: J Nucl Med 2024; 65 (Supplement 2): 241326. https://jnm.snmjournals.org/content/65/supplement_2/241326

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