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Synthetic Ground Truth for Presegmentation of Known Objects for Effortless Pose Estimation

• Authors : Haarslev, Frederik; Juel, William Kristian; Krüger, Norbert ...

Subjects: Object Segmentation; Pose Estimation; Synthetic Ground Truth Generation

• Source: Haarslev, F, Juel, W K, Krüger, N & Bodenhagen, L 2020, Synthetic Ground Truth for Presegmentation of Known Objects for Effortless Pose

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Cone-beam CT-based estimations of prostate motion and dose distortion during radiotherapy

• Authors : Klucznik, Karolina A.; Ravkilde, Thomas; Skouboe, Simon

Subjects: Cone Beam CT; Image guided radiotherapy; Intra-fractional motion

• Source: Klucznik, K A, Ravkilde, T, Skouboe, S, Møller, D S, Hokland, S, Keall, P, Buus, S, Bentzen, L & Poulsen, P R 2025, 'Cone-beam CT-based estimations of prostate motion and dose distortion during

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An active learning approach to train a deep learning algorithm for tumor segmentation from brain MR images

• Authors : Boehringer, Andrew S.; Sanaat, Amirhossein; Arabi, Hossein

Subjects: Active learning; Deep learning; Gliomas

• Source: Boehringer, A S, Sanaat, A, Arabi, H & Zaidi, H 2023, 'An active learning approach to train a deep learning algorithm for tumor segmentation from brain MR images', Insights into Imaging, vol. 14, 141.

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Fully automated accurate patient positioning in computed tomography using anterior–posterior localizer images and a deep neural network:a dual-center study

• Authors : Salimi, Yazdan; Shiri, Isaac; Akavanallaf, Azadeh

Subjects: Computed tomography; CT localizer; Deep learning

• Source: Salimi, Y, Shiri, I, Akavanallaf, A, Mansouri, Z, Arabi, H & Zaidi, H 2023, 'Fully automated accurate patient positioning in computed tomography using anterior–posterior localizer images and a deep

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Utilizing a responsive web portal for studying disc tracing agreement in retinal images

• Authors : Sarhan, Abdullah; Swift, Andrew; Gorner, Adam

• Source: Sarhan, A, Swift, A, Gorner, A, Rokne, J, Alhajj1, R, Docherty, G & Crichton, A 2021, 'Utilizing a responsive web portal for studying disc tracing agreement in retinal images', PLOS ONE, vol. 16, no.

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Development and validation of fully automated robust deep learning models for multi-organ segmentation from whole-body CT images

• Authors : Salimi, Yazdan; Shiri, Isaac; Mansouri, Zahra

Subjects: Computational Models; Computed Tomography; Deep Learning

• Source: Salimi, Y, Shiri, I, Mansouri, Z & Zaidi, H 2025, 'Development and validation of fully automated robust deep learning models for multi-organ segmentation from whole-body CT images', Physica Medica,

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Development and validation of fully automated robust deep learning models for multi-organ segmentation from whole-body CT images

• Authors : Salimi, Yazdan; Shiri, Isaac; Mansouri, Zahra

Subjects: Computational Models; Computed Tomography; Deep Learning

• Source: Salimi, Y, Shiri, I, Mansouri, Z & Zaidi, H 2025, 'Development and validation of fully automated robust deep learning models for multi-organ segmentation from whole-body CT images', Physica Medica,

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cp3-bench:a tool for benchmarking symbolic regression algorithms demonstrated with cosmology

• Authors : Thing, M. E.; Koksbang, S. M.

Subjects: dark energy theory; Machine learning

• Source: Thing, M E & Koksbang, S M 2025, 'cp3-bench : a tool for benchmarking symbolic regression algorithms demonstrated with cosmology', Journal of Cosmology and Astroparticle Physics, vol. 2025, no. 1,

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Tracer-Separator:A Deep Learning Model for Brain PET Dual-Tracer ( 18 F-FDG and Amyloid) Separation

• Authors : Sanaat, Amirhossein; Hu, Yiyi; Boccalini, Cecilia

Subjects: amyloid; deep learning; dual-tracer imaging

• Source: Sanaat, A, Hu, Y, Boccalini, C, Salimi, Y, Mansouri, Z, Teixeira, E P A, Mathoux, G, Garibotto, V & Zaidi, H 2025, 'Tracer-Separator : A Deep Learning Model for Brain PET Dual-Tracer ( 18 F-FDG and

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Evaluating outlier probabilities:assessing sharpness, refinement, and calibration using stratified and weighted measures

• Authors : Röchner, Philipp; Marques, Henrique O.; Campello, Ricardo J.G.B.

Subjects: Anomaly detection; Calibration; Outlier detection

• Source: Röchner, P, Marques, H O, Campello, R J G B & Zimek, A 2024, 'Evaluating outlier probabilities : assessing sharpness, refinement, and calibration using stratified and weighted measures', Data Mining

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