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Dive into the research topics where Daniele Perlo is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
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Projects
- 1 Finished
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Pseudo PET: Pseudo PET imaging of brain tumor hypoxia
Keunen, O. (PI), Niclou, S. (CoPI), Perlo, D. (Participant), Boudissa, S. (Participant) & Kanli, G. (Participant)
1/10/22 → 30/09/24
Project: Research
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Addressing Artefacts in Anatomical MR Images: A k-space-Based Approach
Boudissa, S., Kanli, G., Perlo, D., Jaquet, T. & Keunen, O., May 2024, IEEE International Symposium on Biomedical Imaging, ISBI 2024 - Conference Proceedings. IEEE Computer Society, 5 p. (Proceedings - International Symposium on Biomedical Imaging).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
1 Citation (Scopus) -
Multi-parametric MRI to FMISO PET Synthesis for Hypoxia Prediction in Brain Tumors
Perlo, D., Kanli, G., Boudissa, S., Keunen, O., Mukhopadhyay, A. (Editor), Oksuz, I. (Editor), Engelhardt, S. (Editor), Mehrof, D. (Editor) & Yuan, Y. (Editor), 9 Oct 2024, (Accepted/In press) p. 119-128. 10 p.Research output: Contribution to conference › Paper › peer-review
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Predicting Hypoxia in Brain Tumors from Multiparametric MRI
Perlo, D., Kanli, G., Boudissa, S. & Keunen, O., 25 Jan 2024, 7 p.Research output: Working paper › Preprint
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Applications of AI and HPC in the Health Domain
Oniga, D., Cantalupo, B., Tartaglione, E., Perlo, D., Grangetto, M., Aldinucci, M., Bolelli, F., Pollastri, F., Cancilla, M., Canalini, L., Grana, C., Alcalde, C. M., Cardillo, F. A. & Florea, M., 1 Jan 2022, HPC, Big Data, and AI Convergence Towards Exascale: Challenge and Vision. CRC Press, p. 217-239 23 p.Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review
3 Citations (Scopus) -
Dysplasia Grading of Colorectal Polyps Through Convolutional Neural Network Analysis of Whole Slide Images
Perlo, D., Tartaglione, E., Bertero, L., Cassoni, P. & Grangetto, M., 2022, Proceedings of 2021 International Conference on Medical Imaging and Computer-Aided Diagnosis, MICAD 2021 - Medical Imaging and Computer-Aided Diagnosis. Su, R., Zhang, Y.-D. & Liu, H. (eds.). Springer Science and Business Media Deutschland GmbH, p. 325-334 10 p. (Lecture Notes in Electrical Engineering; vol. 784 LNEE).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
Open Access3 Citations (Scopus)