Complete list of publications can be found in SERVAL, GoogleScholar or ORCID. Here below the latest published articles are displayed.
Serval - Bach Cuadra M. Flux Atom provenant de Serval.
- A dataset of synthetic, maturation-informed magnetic resonance images of the human fetal brain.on 17 April 2025 at 5:10
A dataset of synthetic, maturation-informed magnetic resonance images of the human fetal brain.Lajous H., Le Boeuf Fló A., Gordaliza P.M., Esteban O., Marques F., Dunet V., Koob M., Bach Cuadra M., 2025/04/10. Scientific data, 12 (1) p. 602. Peer-reviewed.[DOI][Pmid][serval:BIB_B31C93DCBC61]
- Assessment of fetal corpus callosum biometry by 3D super-resolution reconstructed T2-weighted magnetic resonance imagingon 28 March 2025 at 6:21
Assessment of fetal corpus callosum biometry by 3D super-resolution reconstructed T2-weighted magnetic resonance imagingLamon Samuel, 2025/02/04., Université de Lausanne, Faculté de biologie et médecine, Bach Cuadra Meritxell (dir.).[URN][DOI][serval:BIB_BC0A9AC1D65D]
- Assessment of fetal corpus callosum biometry by 3D super-resolution reconstructed T2-weighted magnetic resonance imaging.on 21 March 2025 at 6:15
Assessment of fetal corpus callosum biometry by 3D super-resolution reconstructed T2-weighted magnetic resonance imaging.Lamon S., de Dumast P., Sanchez T., Dunet V., Pomar L., Vial Y., Koob M., Bach Cuadra M., 2024. Frontiers in neurology, 15 p. 1358741. Peer-reviewed.[URN][DOI][WoS][Pmid][serval:BIB_569D839EC78C]
- Deep learning microstructure estimation of developing brains from diffusion MRI: A newborn and fetal study.on 25 February 2025 at 6:13
Deep learning microstructure estimation of developing brains from diffusion MRI: A newborn and fetal study.Kebiri H., Gholipour A., Lin R., Vasung L., Calixto C., Krsnik Ž., Karimi D., Bach Cuadra M., 2024/07. Medical image analysis, 95 p. 103186. Peer-reviewed.[URN][DOI][WoS][Pmid][serval:BIB_5DAA21B7E840]
- Structural-based uncertainty in deep learning across anatomical scales: Analysis in white matter lesion segmentation.on 9 January 2025 at 6:09
Structural-based uncertainty in deep learning across anatomical scales: Analysis in white matter lesion segmentation.Molchanova N., Raina V., Malinin A., Rosa F., Depeursinge A., Gales M., Granziera C., Müller H., Graziani M., Cuadra M.B., 2025/01. Computers in biology and medicine, 184 p. 109336. Peer-reviewed.[URN][DOI][Pmid][serval:BIB_17269E6CF957]
- A roadmap towards standardized neuroimaging approaches for human thalamic nuclei.on 22 November 2024 at 16:55
A roadmap towards standardized neuroimaging approaches for human thalamic nuclei.Segobin S., Haast RAM, Kumar V.J., Lella A., Alkemade A., Bach Cuadra M., Barbeau E.J., Felician O., Pergola G., Pitel A.L. et al., 2024/12. Nature reviews. Neuroscience, 25 (12) pp. 792-808. Peer-reviewed.[DOI][WoS][Pmid][serval:BIB_6DA928214590]
- Biometry and volumetry in multi-centric fetal brain MRI: assessing the bias of super-resolution reconstructionon 1 November 2024 at 13:02
Biometry and volumetry in multi-centric fetal brain MRI: assessing the bias of super-resolution reconstructionSanchez Thomas, Mihailov Angeline, Koob Mériam, Girard Nadine, Manchon Aurélie, Valenzuela Ignacio, Gómez-Chiari Marta, Martí Juan Gerard, Pron Alexandre, Eixarch Elisenda et al..[DOI][serval:BIB_9D822D80D09E]
- Maturation-informed synthetic Magnetic Resonance Images of the Developing Human Fetal Brainon 31 October 2024 at 6:13
Maturation-informed synthetic Magnetic Resonance Images of the Developing Human Fetal BrainLajous Hélène, Boeuf Fló Andrés le, Gordaliza Pedro M., Esteban Oscar, Marqués Ferran, Dunet Vincent, Koob Mériam, Cuadra Meritxell Bach.[DOI][serval:BIB_6081E5919797]
- Improving Cross-Domain Brain Tissue Segmentation in Fetal MRI with Synthetic Dataon 24 October 2024 at 5:15
Improving Cross-Domain Brain Tissue Segmentation in Fetal MRI with Synthetic DataZalevskyi Vladyslav, Sanchez Thomas, Roulet Margaux, Aviles Verdera Jordina, Hutter Jana, Kebiri Hamza, Bach Cuadra Meritxell, 2024. pp. 437-447 dans Lecture Notes in Computer Science, Springer Nature Switzerland.[URN][DOI][serval:BIB_973F8E4A8F68]
- FetMRQC: A robust quality control system for multi-centric fetal brain MRI.on 10 September 2024 at 5:24
FetMRQC: A robust quality control system for multi-centric fetal brain MRI.Sanchez T., Esteban O., Gomez Y., Pron A., Koob M., Dunet V., Girard N., Jakab A., Eixarch E., Auzias G. et al., 2024/10. Medical image analysis, 97 p. 103282. Peer-reviewed.[URN][DOI][WoS][Pmid][serval:BIB_6790355DA8EB]
- BMAT: An open-source BIDS managing and analysis tool.on 9 August 2024 at 14:07
BMAT: An open-source BIDS managing and analysis tool.Vanden Bulcke C., Wynen M., Detobel J., La Rosa F., Absinta M., Dricot L., Macq B., Bach Cuadra M., Maggi P., 2022. NeuroImage. Clinical, 36 p. 103252. Peer-reviewed.[URN][DOI][WoS][Pmid][serval:BIB_E3F355A84351]
- Cortical lesions, central vein sign, and paramagnetic rim lesions in multiple sclerosis: Emerging machine learning techniques and future avenues.on 8 August 2024 at 5:32
Cortical lesions, central vein sign, and paramagnetic rim lesions in multiple sclerosis: Emerging machine learning techniques and future avenues.La Rosa F., Wynen M., Al-Louzi O., Beck E.S., Huelnhagen T., Maggi P., Thiran J.P., Kober T., Shinohara R.T., Sati P. et al., 2022. NeuroImage. Clinical, 36 p. 103205. Peer-reviewed.[URN][DOI][WoS][Pmid][serval:BIB_4506B8D09769]
- Connectome Mapper 3: A Flexible and Open-Source Pipeline Software for Multiscale Multimodal Human Connectome Mappingon 18 July 2024 at 5:06
Connectome Mapper 3: A Flexible and Open-Source Pipeline Software for Multiscale Multimodal Human Connectome MappingTourbier Sebastien, Rue-Queralt Joan, Glomb Katharina, Aleman-Gomez Yasser, Mullier Emeline, Griffa Alessandra, Schöttner Mikkel, Wirsich Jonathan, Tuncel M. Anıl, Jancovic Jakub et al., 2022/06/27. Journal of Open Source Software, 7 (74) p. 4248. Peer-reviewed.[URN][DOI][serval:BIB_F8FCF7203C80]
- Simulation-Based Parameter Optimization for Fetal Brain MRI Super-Resolution Reconstructionon 17 July 2024 at 5:19
Simulation-Based Parameter Optimization for Fetal Brain MRI Super-Resolution Reconstructionde Dumast Priscille, Sanchez Thomas, Lajous Hélène, Bach Cuadra Meritxell, 2023. pp. 336-346 dans Lecture Notes in Computer Science, Springer Nature Switzerland.[URN][DOI][serval:BIB_B08F2822DE01]
- Robust thalamic nuclei segmentation from T1-weighted MRI using polynomial intensity transformation.on 15 June 2024 at 5:03
Robust thalamic nuclei segmentation from T1-weighted MRI using polynomial intensity transformation.Vidal J.P., Danet L., Péran P., Pariente J., Bach Cuadra M., Zahr N.M., Barbeau E.J., Saranathan M., 2024/06. Brain structure & function, 229 (5) pp. 1087-1101. Peer-reviewed.[DOI][WoS][Pmid][serval:BIB_9604D6F4D5B0]
- Étude des motifs anatomiques des sillons du lobe temporal à partir de données IRM avec analyse statistiqueon 1 May 2024 at 5:09
Étude des motifs anatomiques des sillons du lobe temporal à partir de données IRM avec analyse statistiqueDe Matos Kevin, 2024., Université de Lausanne, Faculté de biologie et médecine, Bach Cuadra Meritxell (dir.).[serval:BIB_42A29271466E]
- Through-Plane Super-Resolution With Autoencoders in Diffusion Magnetic Resonance Imaging of the Developing Human Brain.on 26 April 2024 at 5:00
Through-Plane Super-Resolution With Autoencoders in Diffusion Magnetic Resonance Imaging of the Developing Human Brain.Kebiri H., Canales-Rodríguez E.J., Lajous H., de Dumast P., Girard G., Alemán-Gómez Y., Koob M., Jakab A., Bach Cuadra M., 2022. Frontiers in neurology, 13 p. 827816. Peer-reviewed.[DOI][WoS][Pmid][serval:BIB_BD4D1BDA9F16]
- Transfer learning with weak labels from radiology reports: application to glioma change detectionon 9 April 2024 at 5:22
Transfer learning with weak labels from radiology reports: application to glioma change detectionDi Noto Tommaso, Bach Cuadra Meritxell, Atat Chirine, Gamito Teiga Eduardo, Hegi Monika, Hottinger Andreas, Hagmann Patric, Richiardi Jonas, 2022..[URN][DOI][serval:BIB_9CC85EE111CA]
- Multiple sclerosis cortical lesion detection with deep learning at ultra-high-field MRI.on 25 January 2024 at 6:42
Multiple sclerosis cortical lesion detection with deep learning at ultra-high-field MRI.La Rosa F., Beck E.S., Maranzano J., Todea R.A., van Gelderen P., de Zwart J.A., Luciano N.J., Duyn J.H., Thiran J.P., Granziera C. et al., 2022/08. NMR in biomedicine, 35 (8) pp. e4730. Peer-reviewed.[URN][DOI][WoS][Pmid][serval:BIB_AA2BF0088C38]
- A New Advanced MRI Biomarker for Remyelinated Lesions in Multiple Sclerosis.on 25 January 2024 at 6:42
A New Advanced MRI Biomarker for Remyelinated Lesions in Multiple Sclerosis.Rahmanzadeh R., Galbusera R., Lu P.J., Bahn E., Weigel M., Barakovic M., Franz J., Nguyen T.D., Spincemaille P., Schiavi S. et al., 2022/09. Annals of neurology, 92 (3) pp. 486-502. Peer-reviewed.[URN][DOI][WoS][Pmid][serval:BIB_A7E8C017F374]
- How far MS lesion detection and segmentation are integrated into the clinical workflow? A systematic review.on 25 January 2024 at 6:38
How far MS lesion detection and segmentation are integrated into the clinical workflow? A systematic review.Spagnolo F., Depeursinge A., Schädelin S., Akbulut A., Müller H., Barakovic M., Melie-Garcia L., Bach Cuadra M., Granziera C., 2023. NeuroImage. Clinical, 39 p. 103491. Peer-reviewed.[URN][DOI][Pmid][serval:BIB_72B208896093]
- A multi-scale probabilistic atlas of the human connectome.on 23 January 2024 at 6:24
A multi-scale probabilistic atlas of the human connectome.Alemán-Gómez Y., Griffa A., Houde J.C., Najdenovska E., Magon S., Cuadra M.B., Descoteaux M., Hagmann P., 2022/08/23. Scientific data, 9 (1) p. 516. Peer-reviewed.[URN][DOI][WoS][Pmid][serval:BIB_493CEE0FC93E]
- FetMRQC: Automated Quality Control for Fetal Brain MRIon 22 December 2023 at 6:50
FetMRQC: Automated Quality Control for Fetal Brain MRISanchez Thomas, Esteban Oscar, Gomez Yvan, Eixarch Elisenda, Cuadra Meritxell Bach, 2023. pp. 3-16 dans Lecture Notes in Computer Science, Springer Nature Switzerland.[DOI][serval:BIB_C79FCE1D3BDA]
- Temporo-basal sulcal connections: a manual annotation protocol and an investigation of sexual dimorphism and heritability.on 14 December 2023 at 6:13
Temporo-basal sulcal connections: a manual annotation protocol and an investigation of sexual dimorphism and heritability.de Matos K., Cury C., Chougar L., Strike L.T., Rolland T., Riche M., Hemforth L., Martin A., Banaschewski T., Bokde ALW et al., 2023/07. Brain structure & function, 228 (6) pp. 1459-1478. Peer-reviewed.[DOI][WoS][Pmid][serval:BIB_A75D868C7257]
- BigBrain-MR: a new digital phantom with anatomically-realistic magnetic resonance properties at 100-µm resolution for magnetic resonance methods development.on 9 December 2023 at 6:14
BigBrain-MR: a new digital phantom with anatomically-realistic magnetic resonance properties at 100-µm resolution for magnetic resonance methods development.Sainz Martinez C., Bach Cuadra M., Jorge J., 2023/06. NeuroImage, 273 p. 120074. Peer-reviewed.[URN][DOI][WoS][Pmid][serval:BIB_87E26260F80E]
- An Anatomically-Informed 3D CNN for Brain Aneurysm Classification with Weak Labelson 31 October 2023 at 6:10
An Anatomically-Informed 3D CNN for Brain Aneurysm Classification with Weak LabelsDi Noto Tommaso, Marie Guillaume, Tourbier Sébastien, Alemán-Gómez Yasser, Saliou Guillaume, Bach Cuadra Meritxell, Hagmann Patric, Richiardi Jonas, 2020. pp. 56-66 dans Machine Learning in Clinical Neuroimaging and Radiogenomics in Neuro-oncology, Springer International Publishing.[URN][DOI][serval:BIB_C85E63E2380A]
- Deep learning microstructure estimation of developing brains from diffusion MRI: a newborn and fetal studyon 21 September 2023 at 4:58
Deep learning microstructure estimation of developing brains from diffusion MRI: a newborn and fetal studyKebiri Hamza, Gholipour Ali, Vasung Lana, Lin Rizhong, Krsnik Željka, Karimi Davood, Bach Cuadra Meritxell.[DOI][Pmid][serval:BIB_4A067369CFE5]
- An automatic multi-tissue human fetal brain segmentation benchmark using the Fetal Tissue Annotation Dataset.on 20 September 2023 at 16:28
An automatic multi-tissue human fetal brain segmentation benchmark using the Fetal Tissue Annotation Dataset.Payette K., de Dumast P., Kebiri H., Ezhov I., Paetzold J.C., Shit S., Iqbal A., Khan R., Kottke R., Grehten P. et al., 2021/07/06. Scientific data, 8 (1) p. 167. Peer-reviewed.[URN][DOI][WoS][Pmid][serval:BIB_6EB3F06B58CA]
- Deep learning methods for diffusion MRI in early development of the human brain: resolution enhancement and model estimationon 13 September 2023 at 5:14
Deep learning methods for diffusion MRI in early development of the human brain: resolution enhancement and model estimationKebiri Hamza, 2023/08/02., Université de Lausanne, Faculté de biologie et médecine, Bach Cuadra Meritxell (dir.).[URN][serval:BIB_B248E402983E]
- A comparative assessment of myelin-sensitive measures in multiple sclerosis patients and healthy subjects.on 31 August 2023 at 4:59
A comparative assessment of myelin-sensitive measures in multiple sclerosis patients and healthy subjects.Rahmanzadeh R., Weigel M., Lu P.J., Melie-Garcia L., Nguyen T.D., Cagol A., La Rosa F., Barakovic M., Lutti A., Wang Y. et al., 2022. NeuroImage. Clinical, 36 p. 103177. Peer-reviewed.[DOI][WoS][Pmid][serval:BIB_460AAADA27D4]
- A novel segmentation framework for uveal melanoma in magnetic resonance imaging based on class activation mapson 10 August 2023 at 4:59
A novel segmentation framework for uveal melanoma in magnetic resonance imaging based on class activation mapsNguyen Huu-Giao, Pica Alessia, Hrbacek Jan, Weber Damien C., La Rosa Francesco, Schalenbourg Ann, Sznitman Raphael, Bach Cuadra Meritxell, 2019/07/08., Medical Imaging with Deep Learning London, 8 ‑ 10 July 2019 pp. 370–379 dans Proceedings of Machine Learning Research, Proceedings of Machine Learning […]
- Development and validation of robust MR image reconstruction and segmentation techniques for the quantitative analysis of the fetal brainon 15 May 2023 at 8:52
Development and validation of robust MR image reconstruction and segmentation techniques for the quantitative analysis of the fetal brainGuerrier de Dumast Priscille, 2023., Université de Lausanne, Faculté de biologie et médecine, Bach Cuadra Meritxell (dir.).[URN][serval:BIB_F3F67E24C1DE]
- Multiple sclerosis cortical and WM lesion segmentation at 3T MRI: a deep learning method based on FLAIR and MP2RAGE.on 14 March 2023 at 5:49
Multiple sclerosis cortical and WM lesion segmentation at 3T MRI: a deep learning method based on FLAIR and MP2RAGE.La Rosa F., Abdulkadir A., Fartaria M.J., Rahmanzadeh R., Lu P.J., Galbusera R., Barakovic M., Thiran J.P., Granziera C., Cuadra M.B., 2020. NeuroImage. Clinical, 27 p. 102335. Peer-reviewed.[URN][DOI][WoS][Pmid][serval:BIB_5FF43232BB1C]
- Towards Automated Brain Aneurysm Detection in TOF-MRA: Open Data, Weak Labels, and Anatomical Knowledge.on 1 March 2023 at 5:47
Towards Automated Brain Aneurysm Detection in TOF-MRA: Open Data, Weak Labels, and Anatomical Knowledge.Di Noto T., Marie G., Tourbier S., Alemán-Gómez Y., Esteban O., Saliou G., Cuadra M.B., Hagmann P., Richiardi J., 2023/01. Neuroinformatics, 21 (1) pp. 21-34. Peer-reviewed.[URN][DOI][WoS][Pmid][serval:BIB_B6A1DE874D8B]
- Multimodal Magnetic Resonance Imaging Depicts Widespread and Subregion Specific Anomalies in the Thalamus of Early-Psychosis and Chronic Schizophrenia Patients.on 19 January 2023 at 5:54
Multimodal Magnetic Resonance Imaging Depicts Widespread and Subregion Specific Anomalies in the Thalamus of Early-Psychosis and Chronic Schizophrenia Patients.Alemán-Gómez Y., Baumgartner T., Klauser P., Cleusix M., Jenni R., Hagmann P., Conus P., Do K.Q., Bach Cuadra M., Baumann P.S. et al., 2023/01/03. Schizophrenia bulletin, 49 (1) pp. 196-207. Peer-reviewed.[DOI][WoS][Pmid][serval:BIB_18D066077BD6]
- Editorial: Computational Neuroimage Analysis Tools for Brain (Diseases) Biomarkers.on 23 November 2022 at 6:15
Editorial: Computational Neuroimage Analysis Tools for Brain (Diseases) Biomarkers.Sima D.M., Bach Cuadra M., Dyrby T.B., Van Leemput K., 2022. Frontiers in neuroscience, 16 p. 841807. Peer-reviewed.[URN][DOI][WoS][Pmid][serval:BIB_DB40F93599BE]
- A Fetal Brain magnetic resonance Acquisition Numerical phantom (FaBiAN).on 23 November 2022 at 6:13
A Fetal Brain magnetic resonance Acquisition Numerical phantom (FaBiAN).Lajous H., Roy C.W., Hilbert T., de Dumast P., Tourbier S., Alemán-Gómez Y., Yerly J., Yu T., Kebiri H., Payette K. et al., 2022/05/23. Scientific reports, 12 (1) p. 8682. Peer-reviewed.[URN][DOI][WoS][Pmid][serval:BIB_9F910B893D7D]
- Chronic White Matter Inflammation and Serum Neurofilament Levels in Multiple Sclerosis.on 21 November 2022 at 7:31
Chronic White Matter Inflammation and Serum Neurofilament Levels in Multiple Sclerosis.Maggi P., Kuhle J., Schädelin S., van der Meer F., Weigel M., Galbusera R., Mathias A., Lu P.J., Rahmanzadeh R., Benkert P. et al., 2021/08/10. Neurology, 97 (6) pp. e543-e553. Peer-reviewed.[URN][DOI][WoS][Pmid][serval:BIB_6A4C8678004D]
- GAMER MRI: Gated-attention mechanism ranking of multi-contrast MRI in brain pathology.on 21 November 2022 at 7:30
GAMER MRI: Gated-attention mechanism ranking of multi-contrast MRI in brain pathology.Lu P.J., Yoo Y., Rahmanzadeh R., Galbusera R., Weigel M., Ceccaldi P., Nguyen T.D., Spincemaille P., Wang Y., Daducci A. et al., 2021. NeuroImage. Clinical, 29 p. 102522. Peer-reviewed.[URN][DOI][WoS][Pmid][serval:BIB_39876666592D]
- Model-informed machine learning for multi-component T2 relaxometry.on 21 November 2022 at 7:09
Model-informed machine learning for multi-component T<sub>2</sub> relaxometry.Yu T., Canales-Rodríguez E.J., Pizzolato M., Piredda G.F., Hilbert T., Fischi-Gomez E., Weigel M., Barakovic M., Bach Cuadra M., Granziera C. et al., 2021/04. Medical image analysis, 69 p. 101940. Peer-reviewed.[URN][DOI][WoS][Pmid][serval:BIB_934FD7FA4F63]
- Diagnostic surveillance of high-grade gliomas: towards automated change detection using radiology report classificationon 8 June 2022 at 4:36
Diagnostic surveillance of high-grade gliomas: towards automated change detection using radiology report classificationDi Noto Tommaso, Atat Chirine, Teiga Eduardo Gamito, Hegi Monika, Hottinger Andreas, Bach Cuadra Meritxell, Hagmann Patric, Richiardi Jonas, 2022/01/01. pp. 423-436 dans Machine Learning and Principles and Practice of Knowledge Discovery in Databases. ECML PKDD 2021., Communications in Computer and […]
- Quantitative Evaluation of Enhanced Multi-plane Clinical Fetal Diffusion MRI with a Crossing-Fiber Phantomon 1 June 2022 at 4:39
Quantitative Evaluation of Enhanced Multi-plane Clinical Fetal Diffusion MRI with a Crossing-Fiber PhantomKebiri Hamza, Lajous Hélène, Alemán-Gómez Yasser, Girard Gabriel, Rodríguez Erick Canales, Tourbier Sébastien, Pizzolato Marco, Ledoux Jean-Baptiste, Fornari Eleonora, Jakab András et al., 2021. pp. 12-22 dans Computational Diffusion MRI, Springer International […]
- Ophthalmic Magnetic Resonance Imaging: Where Are We (Heading To)?on 8 March 2022 at 5:33
Ophthalmic Magnetic Resonance Imaging: Where Are We (Heading To)?Niendorf T., Beenakker J.M., Langner S., Erb-Eigner K., Bach Cuadra M., Beller E., Millward J.M., Niendorf T.M., Stachs O., 2021/09. Current eye research, 46 (9) pp. 1251-1270. Peer-reviewed.[DOI][WoS][Pmid][serval:BIB_0D766C431EA3]
- Multi-view convolutional neural networks for automated ocular structure and tumor segmentation in retinoblastoma.on 12 January 2022 at 6:10
Multi-view convolutional neural networks for automated ocular structure and tumor segmentation in retinoblastoma.Strijbis VIJ, de Bloeme C.M., Jansen R.W., Kebiri H., Nguyen H.G., de Jong M.C., Moll A.C., Bach-Cuadra M., de Graaf P., Steenwijk M.D., 2021/07/16. Scientific reports, 11 (1) p. 14590. Peer-reviewed.[URN][DOI][WoS][Pmid][serval:BIB_61A3D7FC211B]
- GAMER-MRI in Multiple Sclerosis Identifies the Diffusion-Based Microstructural Measures That Are Most Sensitive to Focal Damage: A Deep-Learning-Based Analysis and Clinico-Biological Validation.on 12 January 2022 at 6:10
GAMER-MRI in Multiple Sclerosis Identifies the Diffusion-Based Microstructural Measures That Are Most Sensitive to Focal Damage: A Deep-Learning-Based Analysis and Clinico-Biological Validation.Lu P.J., Barakovic M., Weigel M., Rahmanzadeh R., Galbusera R., Schiavi S., Daducci A., La Rosa F., Bach Cuadra M., Sandkühler R. et al., 2021. Frontiers in neuroscience, 15 p. 647535. […]
- Myelin and axon pathology in multiple sclerosis assessed by myelin water and multi-shell diffusion imaging.on 12 January 2022 at 6:08
Myelin and axon pathology in multiple sclerosis assessed by myelin water and multi-shell diffusion imaging.Rahmanzadeh R., Lu P.J., Barakovic M., Weigel M., Maggi P., Nguyen T.D., Schiavi S., Daducci A., La Rosa F., Schaedelin S. et al., 2021/07/28. Brain, 144 (6) pp. 1684-1696. Peer-reviewed.[URN][DOI][WoS][Pmid][serval:BIB_1C5A25DB7291]
- Fetal Brain Biometric Measurements on 3D Super-Resolution Reconstructed T2-Weighted MRI: An Intra- and Inter-observer Agreement Study.on 4 September 2021 at 5:08
Fetal Brain Biometric Measurements on 3D Super-Resolution Reconstructed T2-Weighted MRI: An Intra- and Inter-observer Agreement Study.Khawam M., de Dumast P., Deman P., Kebiri H., Yu T., Tourbier S., Lajous H., Hagmann P., Maeder P., Thiran J.P. et al., 2021. Frontiers in pediatrics, 9 p. 639746. Peer-reviewed.[URN][DOI][WoS][Pmid][serval:BIB_0C9548890931]
- MPRAGE to MP2RAGE UNI translation via generative adversarial network improves the automatic tissue and lesion segmentation in multiple sclerosis patients.on 29 May 2021 at 4:32
MPRAGE to MP2RAGE UNI translation via generative adversarial network improves the automatic tissue and lesion segmentation in multiple sclerosis patients.La Rosa F., Yu T., Barquero G., Thiran J.P., Granziera C., Bach Cuadra M., 2021/05. Computers in biology and medicine, 132 p. 104297. Peer-reviewed.[DOI][WoS][Pmid][serval:BIB_F08CC4CD5E7D]
- Evolution of Cortical and White Matter Lesion Load in Early-Stage Multiple Sclerosis: Correlation With Neuroaxonal Damage and Clinical Changes.on 30 April 2021 at 5:09
Evolution of Cortical and White Matter Lesion Load in Early-Stage Multiple Sclerosis: Correlation With Neuroaxonal Damage and Clinical Changes.Todea R.A., Lu P.J., Fartaria M.J., Bonnier G., Du Pasquier R., Krueger G., Bach Cuadra M., Psychogios M.N., Kappos L., Kuhle J. et al., 2020. Frontiers in neurology, 11 p. 973. Peer-reviewed.[URN][DOI][WoS][Pmid][serval:BIB_368B9441C688]
- Automated Detection of Cortical Lesions in Multiple Sclerosis Patients with 7T MRIon 6 February 2021 at 6:09
Automated Detection of Cortical Lesions in Multiple Sclerosis Patients with 7T MRILa Rosa Francesco, Beck Erin S., Abdulkadir Ahmed, Thiran Jean-Philippe, Reich Daniel S., Sati Pascal, Bach Cuadra Meritxell, 2020/10/04., 23rd International Conference, Lima, Peru, October 4–8, 2020, Proceedings, Part IV dans Medical Image Computing and Computer Assisted Intervention – MICCAI 2020. Peer-reviewed, Prof. Anne L. […]