A Deep Graph Cut Model for 3D Brain Tumor Segmentation
Conference paper
De, A., Tiwari, M., Grisan, E. and Chowdhury, A.S. (2022). A Deep Graph Cut Model for 3D Brain Tumor Segmentation. 44th International Engineering in Medicine and Biology Conference (EMBC 2022). Glasgow (UK) 11 - 15 Jul 2022 Institute of Electrical and Electronics Engineers (IEEE).
| Authors | De, A., Tiwari, M., Grisan, E. and Chowdhury, A.S. |
|---|---|
| Type | Conference paper |
| Abstract | Brain tumor segmentation plays a key role in tumor diagnosis and surgical planning. In this paper, we propose a solution to the 3D brain tumor segmentation problem using deep learning and graph cut from the MRI data. In particular, the probability maps of a voxel to belong to the object (tumor) and background classes from the UNet are used to improve the energy function of the graph cut. We derive new expressions for the data term, the region term and the weight factor balancing the data term and the region term for individual voxels in our proposed model. We validate the performance of our model on the publicly available BRATS 2018 dataset. Our segmentation accuracy with a dice similarity score of 0.92 is found to be higher than that of the graph cut and the UNet applied in isolation as well as over a number of state of the art approaches. |
| Year | 2022 |
| Publisher | Institute of Electrical and Electronics Engineers (IEEE) |
| Web address (URL) | https://embc.embs.org/2022/ |
| Accepted author manuscript | License File Access Level Open |
| Publication dates | |
| 15 Jul 2022 | |
| Publication process dates | |
| Accepted | 04 Apr 2022 |
| Deposited | 29 Apr 2022 |
| Additional information | © 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
Permalink -
https://openresearch.lsbu.ac.uk/item/8zqz3
Download files
141
total views164
total downloads1
views this month1
downloads this month
Export as
Related outputs
Study Protocol: Evaluating artificial intelligence-driven stress echocardiography analysis system (EASE study): mixed method study.
Mahdavi, M., Thomas, N., Flood, C., Stewart-Lord, A., Baillie, L., Grisan, E., Callaghan, P., Panayotova, R, Hothi, S, Griffith, V., Jayadev, S. and Frings, D. Study Protocol: Evaluating artificial intelligence-driven stress echocardiography analysis system (EASE study): mixed method study. BMJ Open.A Consensus Mechanism to Improve Prediction of Cortical Bone Properties using Ultrafast Ultrasound Acquisition
Abdelreheem, H., Grisan, E., Dryburgh, P., Peralta, L. and Harput, S. (2024). A Consensus Mechanism to Improve Prediction of Cortical Bone Properties using Ultrafast Ultrasound Acquisition. IEEE Access. https://doi.org/10.1109/ACCESS.2024.3404644A pragmatic trial of an Artificial intelligence DRiven appOInTment maNagEment SyStem (ADROITNESS) in NHS outpatient departments: WP3 REPORT
Thomas, N., Frings, D., Flood, C., Grisan, E., Wood, K., Daly, N. and Sharma, S. (2024). A pragmatic trial of an Artificial intelligence DRiven appOInTment maNagEment SyStem (ADROITNESS) in NHS outpatient departments: WP3 REPORT. London South Bank University.Artificial Intelligence and Endo-Histo-OMICs: New Dimensions of Precision Endoscopy and Histology in Inflammatory Bowel Disease
Iacucci, M., Santacroce, G., Zanmarchi, I., Maeda, Y., del Amor, R., Meseguer, P., Kolawole, B., Chaudhari, U., Di Sabatino, A., Danese, S., Mori, Y., Grisan, E., Naranjo, V. and Ghosh, S. (2024). Artificial Intelligence and Endo-Histo-OMICs: New Dimensions of Precision Endoscopy and Histology in Inflammatory Bowel Disease. The Lancet Gastroenterology & Hepatology. 9 (8), pp. 758-772. https://doi.org/10.1016/S2468-1253(24)00053-0Deep learning analysis of plasma emissions: A potential system for monitoring methane and hydrogen in the pyrolysis processes
Salimian, A. and Grisan, E. (2024). Deep learning analysis of plasma emissions: A potential system for monitoring methane and hydrogen in the pyrolysis processes. International Journal of Hydrogen Energy. 58, pp. 1030-1043. https://doi.org/10.1016/j.ijhydene.2024.01.251A pragmatic trial of an Artificial intelligence DRiven appOInTment maNagEment SyStem (ADROITNESS) in NHS outpatient departments: WP1 Accuracy - Phase 2b Evaluation Report
Thomas, N., Frings, D., Flood, C., Grisan, E., Wood, K., Daly, N. and Sharma, S. (2023). A pragmatic trial of an Artificial intelligence DRiven appOInTment maNagEment SyStem (ADROITNESS) in NHS outpatient departments: WP1 Accuracy - Phase 2b Evaluation Report. London South Bank University.A pragmatic trial of an Artificial intelligence DRiven appOInTment maNagEment SyStem (ADROITNESS) in NHS outpatient departments: WP1 Accuracy - Phase 2A Evaluation Report
Thomas, N., Frings, D., Flood, C., Grisan, E., Wood, K., Daly, N. and Sharma, S. (2023). A pragmatic trial of an Artificial intelligence DRiven appOInTment maNagEment SyStem (ADROITNESS) in NHS outpatient departments: WP1 Accuracy - Phase 2A Evaluation Report. London South Bank University.Age-related changes in the primary auditory cortex of newborn, adults and aging bottlenose dolphins (Tursiops truncatus) are located in the upper cortical layers
Graïc, J., Corain, L, Finos, L., Vadori, V., Grisan, E., Gerussi, T., Orekhova, K., Centelleghe, C, Cozzi, B. and Peruffo, A. (2023). Age-related changes in the primary auditory cortex of newborn, adults and aging bottlenose dolphins (Tursiops truncatus) are located in the upper cortical layers. Frontiers in Neuroanatomy. 17. https://doi.org/10.3389/fnana.2023.1330384Cortical Bone Thickness Assessment from Multi-frequency Ultrasound RF Data using a Convolutional Architecture with Multi-head Attention
Sultan, H.H., Grisan, E., Dryburgh, P., Peralta, L. and Harput, S. (2023). Cortical Bone Thickness Assessment from Multi-frequency Ultrasound RF Data using a Convolutional Architecture with Multi-head Attention. 2023 IEEE International Ultrasonics Symposium (IUS). Montreal, QC, Canada 03 - 08 Sep 2023 IEEE. https://doi.org/10.1109/ius51837.2023.10307373A novel DSP zebrafish model reveals training- and drug-induced modulation of arrhythmogenic cardiomyopathy phenotypes
Celeghin, R., Risato, G., Beffagna, G., Cason, M., Bueno Marinas, M., Della Barbera, M., Facchinello, N., Giuliodori, A., Brañas Casas, R., Caichiolo, M., Vettori, V., Grisan, E., Rizzo, S., Dalla Valle, L., Francesco Argenton, Thiene, G., Tiso, N., Pilichou, K. and Basso, N. (2023). A novel DSP zebrafish model reveals training- and drug-induced modulation of arrhythmogenic cardiomyopathy phenotypes. Cell Death Discovery . 9 (441). https://doi.org/10.1038/s41420-023-01741-2Mr-Nom: Multi-Scale Resolution of Neuronal Cells in Nissl-Stained Histological Slices Via Deliberate over-Segmentation and Merging
Vadori, V., Graïc, J-M., Finos, L., Corain, L., Peruffo, A. and Grisan, E. (2023). Mr-Nom: Multi-Scale Resolution of Neuronal Cells in Nissl-Stained Histological Slices Via Deliberate over-Segmentation and Merging. 2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI). Cartegena de Indias, Colombia 18 - 21 Apr 2023 IEEE. https://doi.org/10.1109/isbi53787.2023.10230352Cytoarchitectureal changes in hippocampal subregions of the NZB/W F1 mouse model of lupus
Graïc, J-M., Finos, L., Cozzi, B., Luisetto, R., Gerussi, T, Doria, A., Vadori, V., Grisan, E., Corain, L. and Peruffo, A. (2023). Cytoarchitectureal changes in hippocampal subregions of the NZB/W F1 mouse model of lupus. Brain, Behavior and Immunity. 32 (October), p. 100662. https://doi.org/10.1016/j.bbih.2023.100662Artificial Intelligence enabled histological prediction of remission or activity and clinical outcomes in ulcerative colitis
Iacucci, M., Parigi, T.L., del Amor, R., Meseguer, P., Mandelli, G., Bozzola, A., Bazarova, A., Bhandari, P., Bisschops, R., Danese, S., De Hertogh, G., Ferraz, J.G., Goetz, M., Grisan, E., Gui, X., Hayee, B., Kiesslich, R., Lazarev, M., Panaccione, R., Parra-Blanco, A., Pastorelli, L., Rath, T., Royset, E.S., Tontini, G.E., Vath, M., Zardo, D., Ghosh, S., Naranjo, V. and Villanacci, V. (2023). Artificial Intelligence enabled histological prediction of remission or activity and clinical outcomes in ulcerative colitis. Gastroenterology. https://doi.org/10.1053/j.gastro.2023.02.031A pragmatic trial of an Artificial intelligence DRiven appOInTment maNagEment SyStem (ADROITNESS) in NHS outpatient departments
Thomas, N., Frings, D., Flood, C., Grisan, E., Wood, K., Daly, N. and Sharma, S. (2022). A pragmatic trial of an Artificial intelligence DRiven appOInTment maNagEment SyStem (ADROITNESS) in NHS outpatient departments. London South Bank University.A pragmatic trial of an Artificial intelligence DRiven appOInTment maNagEment SyStem (ADROITNESS) in NHS outpatient departments: WP1 Accuracy - Phase 1 Evaluation Report
Thomas, N., Frings, D., Flood, C., Grisan, E., Wood, K., Daly, N. and Sharma, S. (2022). A pragmatic trial of an Artificial intelligence DRiven appOInTment maNagEment SyStem (ADROITNESS) in NHS outpatient departments: WP1 Accuracy - Phase 1 Evaluation Report. London South Bank University.Estimation of Cortical Bone Strength Using CNN-based Regression Model
Sultan, Hossam H., Grisan, E., Peralta, L. and Harput, S. (2022). Estimation of Cortical Bone Strength Using CNN-based Regression Model. 2022 IEEE International Ultrasonics Symposium (IUS). Venice, Italy 10 - 13 Oct 2022 Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/ius54386.2022.9957568Motion Correction Using Deep Learning Neural Networks - Effects of Data Representation
Zaydullin, R., Bharath, A.A., Grisan, E., Christensen-Jeffries, K., Bai, W. and Tang, M-X. (2022). Motion Correction Using Deep Learning Neural Networks - Effects of Data Representation. 2022 IEEE International Ultrasonics Symposium (IUS). Venice, Italy 10 - 13 Oct 2022 Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/ius54386.2022.9958903Computer-Aided Imaging Analysis of Probe-Based Confocal Laser Endomicroscopy With Molecular Labeling and Gene Expression Identifies Markers of Response to Biological Therapy in IBD Patients: The Endo-Omics Study
Iacucci, M., Jeffery, L., Acharjee, A., Grisan, E., Buda, A., Nardone, O.M., Smith, S.C.L., Labarile, N., Zardo, D., Ungar, B., Hunter, S., Mao, R., Cannatelli,R., Shivaji, U.N., Parigi, T.L., Reynolds, G.M., Gkoutos, G.V. and Ghosh, S. (2022). Computer-Aided Imaging Analysis of Probe-Based Confocal Laser Endomicroscopy With Molecular Labeling and Gene Expression Identifies Markers of Response to Biological Therapy in IBD Patients: The Endo-Omics Study. Inflammatory Bowel Diseases. 2022 (izac233), pp. 1-12. https://doi.org/0.1093/ibd/izac233A Virtual Chromoendoscopy Artificial Intelligence system to detect endoscopic and histologic activity/remission and predict clinical outcomes in Ulcerative Colitis
Iacucci, M, Cannatelli, R, Parigi,T.L., Nardone, O.M., Tontini, G.E., Labarile, N, Buda, A., Rimondi, A., Bazarova, A., Bisschops, R., del Amor, R., Meseguer, P., Naranjo, V., PICaSSO Group, Ghosh, S. and Grisan, E. (2022). A Virtual Chromoendoscopy Artificial Intelligence system to detect endoscopic and histologic activity/remission and predict clinical outcomes in Ulcerative Colitis. Endoscopy. https://doi.org/10.1055/a-1960-3645Accelerating colloidal quantum dot innovation with algorithms and automation
Howes, P., Munyebvu, N., Lane, E. and Grisan, E. (2022). Accelerating colloidal quantum dot innovation with algorithms and automation. Materials Advances. https://doi.org/10.1039/d2ma00468bConstrained Multiple Instance Learning for Ulcerative Colitis prediction using Histological Images
del Amor, R., Meseguera, P., Parigi, T.L., Villanacci, V., Colomer, A., Launet, L., Bazarova, A., Tontini, G.E., Bisschops, R., de Hertogh, G., Ferraz, J.G., Götz, M., Gui, Xi., Hayeem, B., Lazarev, M., Panaccione, R., Parra-Blanco, A., Bhandari, P., Pastorelli, L., Rath, T., Synnøve Røyset, E., Vieth, M., Zardo, D., Grisan, E., Ghosh, S., Iacucci, M. and Naranjo, V. (2022). Constrained Multiple Instance Learning for Ulcerative Colitis prediction using Histological Images. Computer methods and programs in biomedicine. 224, p. 107012. https://doi.org/10.1016/j.cmpb.2022.107012A Virtual Chromoendoscopy Artificial Intelligence System To Detect Endoscopic And Histologic Remission In Ulcerative Colitis
Iacucci M., Cannatelli, R., Parigi, T.L., Buda, A., Labarile, N., Nardone, O. M., Tontini, G. E., Rimondi, A., Bazarova, A., Bhandari, P., Bisschops, R., De Hertogh, G., Del Amor, R., Ferraz, J. G., Goetz, M., Gui, S. X., Hayee, B., Kiesslich, R., Lazarev, M., Naranjo, V., Panaccione, R., Parra-Blanco, A., Pastorelli, L., Rath, T., Røyset, E. S., Vieth, M., Villanacci, V., Zardo, D., Ghosh, S. and Grisan, E. (2022). A Virtual Chromoendoscopy Artificial Intelligence System To Detect Endoscopic And Histologic Remission In Ulcerative Colitis. Digestive Disease Week - DDW 2022. San Diego (CA) 21 - 24 May 2022A Virtual Chromoendoscopy Artificial Intelligence System To Detect Endoscopic And Histologic Remission In Ulcerative Colitis
Iacucci, M., Cannatelli, R., Parigi, T.L., Buda, A., Labarile, N., Nardone, O.M., Tontini, G.E., Rimondi, A., Bazarova, A., Bhandari, P., Bisschops, R., De Hertogh, G., del Amor, R., Ferraz, J.G, Goetz, M., Gui, X., Hayee, B., Kiesslich, R., Lazarev, M., Naranjo, V., Panaccione, R., Parra-Blanco, A., Pastorelli, L., Rath, T., Røyset, E.S, Vieth, M., Villanacci, V., Zardo, D., Ghosh, S. and Grisan, E. (2022). A Virtual Chromoendoscopy Artificial Intelligence System To Detect Endoscopic And Histologic Remission In Ulcerative Colitis. ESGE Days 2022. 28 Apr 2022 Georg Thieme Verlag KG. https://doi.org/10.1055/s-0042-1744593OP16 The first virtual chromoendoscopy artificial intelligence system to detect endoscopic and histologic remission in Ulcerative Colitis
Iacucci, M, Cannatelli, R, Parigi, TL, Buda, A, Labarile, N, Nardone, OM, Tontini, GE, Rimondi, A, Bazarova, A, Bhandari, P, Bisschops, R, De Hertogh, G, Del Amor, R, Ferraz, JG, Goetz, M, Gui, X, Hayee, B, Kiesslich, R, Lazarev, M, Naranjo, V, Panaccione, R, Parra-Blanco, A, Pastorelli, L, Rath, T, Røyset, ES, Vieth, M, Villanacci, V, Zardo, D, Ghosh, S and Grisan, E. (2022). OP16 The first virtual chromoendoscopy artificial intelligence system to detect endoscopic and histologic remission in Ulcerative Colitis. 17th Congress of ECCO - European Crohn’s and Colitis Organisation. 16 - 19 Feb 2022 Oxford University Press (OUP). https://doi.org/10.1093/ecco-jcc/jjab232.015OP15 A new simplified histology artificial intelligence system for accurate assessment of remission in Ulcerative Colitis
Villanacci, V, Parigi, TL, Del Amor, R, Mesguer Esbrì, P, Gui, X, Bazarova, A, Bhandari, P, Bisschops, R, Danese, S, De Hertogh, G, G Ferraz, JG, Götz, M, Grisan, E., Hayee, B, Kiesslich, R, Lazarev, M, Mandelli, G, Monica, MAT, Panaccione, R, Parra-Blanco, A, Pastorelli, L, Rath, T, Røyset, ES, Shivaji, U, Tontini, GE, Vieth, M, Zardo, D, Ghosh, S, Naranjo, V and Iacucci, M (2022). OP15 A new simplified histology artificial intelligence system for accurate assessment of remission in Ulcerative Colitis. 17th Congress of ECCO - European Crohn’s and Colitis Organisation. 16 - 19 Feb 2022 Oxford University Press (OUP). https://doi.org/10.1093/ecco-jcc/jjab232.014Predicting functional impairment trajectories in amyotrophic lateral sclerosis: a probabilistic, multifactorial model of disease progression.
Tavazzi, E., Daberdaku, S., Zandonà, A., Vasta, R., Nefussy, B., Lunetta, C., Mora, G., Mandrioli, J., Grisan, E., Tarlarini, C., Calvo, A., Moglia, C., Drory, V., Gotkine, M., Chiò, A., Di Camillo, B. and Piemonte, Valle d’Aosta Register for ALS (PARALS), for the Emilia Romagna Registry for ALS (ERRALS) (2022). Predicting functional impairment trajectories in amyotrophic lateral sclerosis: a probabilistic, multifactorial model of disease progression. Journal of neurology. https://doi.org/10.1007/s00415-022-11022-0An Adaptive Registration Algorithm for Zebrafish Larval Brain Images
Deb, S, Tiso, N, Grisan, E. and Chowdhury, A.S. (2022). An Adaptive Registration Algorithm for Zebrafish Larval Brain Images. Computer methods and programs in biomedicine. 216, p. 106658. https://doi.org/10.1016/j.cmpb.2022.106658PICaSSO Histologic Remission Index (PHRI) in Ulcerative Colitis – Development of a Novel Simplified Histological Score for Monitoring Mucosal Healing and Predicting Clinical Outcomes and its Applicability in an Artificial Intelligence System
Gui, X., Bazarova, A., del Amor, R., Vieth, M., de Hertogh, G., Villanacci, V., Zardo, D., Parigi, T. L., Røyset, E., Shivaji, U., Monica, M. A.T., Mandelli, G., Bhandari, P., Danese, S., Ferraz, J., Hayee, B., Lazarev, M., Parra-Blanco, A., Pastorelli, L., Panaccione, R., Rath, T., Tontini, G.E., Ralf, H., Bisschops, R., Grisan, E., Naranjo, V., Ghosh, S. and Iacucci, M. (2022). PICaSSO Histologic Remission Index (PHRI) in Ulcerative Colitis – Development of a Novel Simplified Histological Score for Monitoring Mucosal Healing and Predicting Clinical Outcomes and its Applicability in an Artificial Intelligence System. Gut. https://doi.org/10.1136/gutjnl-2021-326376The primary visual cortex of Cetartiodactyls: organization, cytoarchitectonics and comparison with perissodactyls and primates.
Graïc, J., Peruffo, A., Corain, L., Finos, L., Grisan, E. and Cozzi, B. (2021). The primary visual cortex of Cetartiodactyls: organization, cytoarchitectonics and comparison with perissodactyls and primates. Brain structure & function. 227, p. 1195–1225. https://doi.org/10.1007/s00429-021-02392-8Deep learning for the prediction of treatment response in depression
Squarcina, L., Villa, F.M., Nobile, M., Grisan, E. and Brambilla, P. (2021). Deep learning for the prediction of treatment response in depression. Journal of Affective Disorders. 281, pp. 618-622. https://doi.org/10.1016/j.jad.2020.11.104Response to Biologics in Ibd Patients Assessed by Computerized Image Analysis of Probe Based Confocal Laser Endomicroscopy With Molecular Labeling
Iacucci, M, Grisan, E, Labarile, N, Nardone, OM, Smith, SCL, Jeffery, L, Cannatelli, R, Ghosh, S and Buda, A (2021). Response to Biologics in Ibd Patients Assessed by Computerized Image Analysis of Probe Based Confocal Laser Endomicroscopy With Molecular Labeling. ESGE Days 2021. Virtual 25 - 27 Mar 2021 Georg Thieme Verlag KG. https://doi.org/10.1055/s-0041-1724759Deep-Learning Estimation of Perfusion Kinetic Parameters in Contrast-Enhanced Ultrasound Imaging
Grisan, E., Harput, S., Raffeiner, B., Fiocco, U. and Stramare, R. (2021). Deep-Learning Estimation of Perfusion Kinetic Parameters in Contrast-Enhanced Ultrasound Imaging. IEEE International Symposium on Biomedical Imaging - IEEE ISBI. Nice 13 - 16 Apr 2021 Institute of Electrical and Electronics Engineers (IEEE).The claustrum of the sheep and its connections to the visual cortex
Pirone, A., Graïc, J., Grisan, E. and Cozzi, B. (2020). The claustrum of the sheep and its connections to the visual cortex. Journal of Anatomy. 238 (1), pp. 1-12. https://doi.org/10.1111/joa.13302Is machine learning prediction of Aβ positivity consistent? An assessment of multiple datasets
Grecchi, E., Grisan, E., Buckley, C. and Wolber, J. (2020). Is machine learning prediction of Aβ positivity consistent? An assessment of multiple datasets. Wiley. https://doi.org/10.1002/alz.040990Single- and Multi-Distribution Dimensionality Reduction Approaches for a Better Data Structure Capturing
Hajderanj, L., Chen, D., Grisan, E. and Dudley-McEvoy, S (2020). Single- and Multi-Distribution Dimensionality Reduction Approaches for a Better Data Structure Capturing. IEEE Access. 8, pp. 207141 - 207155. https://doi.org/10.1109/ACCESS.2020.3038460Multi-aspect testing and ranking inference to quantify dimorphism in the cytoarchitecture of cerebellum of male, female and intersex individuals: a model applied to bovine brains.
Corain, L., Grisan, E., Graïc, J., Carvajal-Schiaffino, R., Cozzi, B. and Peruffo, A. (2020). Multi-aspect testing and ranking inference to quantify dimorphism in the cytoarchitecture of cerebellum of male, female and intersex individuals: a model applied to bovine brains. Brain structure & function. https://doi.org/10.1007/s00429-020-02147-xPreface to: EndoCV2020Computer Vision in Endoscopy
Ali, S, Daul, C, Rittscher, J, Stoyanov, D and Grisan, E (2020). Preface to: EndoCV2020Computer Vision in Endoscopy. CEUR Workshop Proceedings. 2595.An assay system to evaluate riboflavin/UV-A corneal phototherapy efficacy in a porcine corneal organ culture model
Perazzi, A, Gomiero, C, Corain, Livio, Iacopetti, Ilaria, Grisan, Enrico, Lombardo, Marco, Lombardo, Giuseppe, Salvalaio, Gianni, Contin, Roberta, Patruno, Marco, Martinello, Tiziana and Peruffo, Antonella (2020). An assay system to evaluate riboflavin/UV-A corneal phototherapy efficacy in a porcine corneal organ culture model. Animals. 10, pp. 1-16. https://doi.org/10.3390/ani10040730An objective comparison of detection and segmentation algorithms for artefacts in clinical endoscopy
Ali, S., Zhou, F., Braden, B., Bailey, A., Yang, S., Cheng, G., Zhang, P., Li, X., Kayser, M., Soberanis-Mukul, R., Albarqouni, S., Wang, X., Wang, C., Watanabe, S., Oksuz, I., Ning, Q., Yang, S., Khan, M.A., Gao, X., Realdon, S., Loshchenov, M., Schnabel, J., East, J., Wagnieres, G., Loschenov, V., Grisan, E., Daul, C., Blondel, W. and Rittscher, J. (2020). An objective comparison of detection and segmentation algorithms for artefacts in clinical endoscopy. Scientific Reports. 10, p. 2748. https://doi.org/10.1038/s41598-020-59413-5In-vivo Barretts esophagus digital pathology stage classification through feature enhancement of confocal laser endomicroscopy
Ghatwary, N, Ahmed, A, Grisan, E, Jalab, H, Bidaut, L and Ye, X (2019). In-vivo Barretts esophagus digital pathology stage classification through feature enhancement of confocal laser endomicroscopy. J Med Imaging (Bellingham). 6 (1). https://doi.org/https://www.doi.org/10.1117/1.JMI.6.1.014502Real-time diameter of the fetal aorta from ultrasound
Savioli, Nicolò, Grisan, Enrico, Visentin, Silvia, Cosmi, Erich, Montana, Giovanni and Lamata, Pablo (2019). Real-time diameter of the fetal aorta from ultrasound. Neural Computing and Applications. https://doi.org/10.1007/s00521-019-04646-3Does Quantification of Carotid Plaque Surface Irregularities Better Detect Symptomatic Plaques Compared to the Subjective Classification?
Rafailidis, V., Chryssogonidis, I., Grisan, E., Xerras, C., Cheimariotis, G-A., Tegos, T., Rafailidis, D., Sidhu, P. and Charitanti-Kouridou, A. (2019). Does Quantification of Carotid Plaque Surface Irregularities Better Detect Symptomatic Plaques Compared to the Subjective Classification? Journal of Ultrasound in Medicine. 38 (12), pp. 3163-3171. https://doi.org/10.1002/jum.15017An ultrasonographic multiparametric carotid plaque risk index associated with cerebrovascular symptomatology: A study comparing color Doppler imaging and contrast-enhanced ultrasonography
Rafailidis, V., Chryssogonidis, I., Xerras, C., Grisan, E., Cheimariotis, G-A., Tegos, T., Rafailidis, P.S., Sidhu, P.S. and Charitanti-Kouridou, A. (2019). An ultrasonographic multiparametric carotid plaque risk index associated with cerebrovascular symptomatology: A study comparing color Doppler imaging and contrast-enhanced ultrasonography. American Journal of Neuroradiology. 40 (6), pp. 1022-1028. https://doi.org/10.3174/ajnr.A6056The motor cortex of the sheep: laminar organization, projections and diffusion tensor imaging of the intracranial pyramidal and extrapyramidal tracts
Peruffo, A., Corain, L., Bombardi, C., Centelleghe, C., Grisan, E., Graïc, J-M, Bontempi, P., Grandis, A. and Cozzi, B. (2019). The motor cortex of the sheep: laminar organization, projections and diffusion tensor imaging of the intracranial pyramidal and extrapyramidal tracts. Brain Structure and Function. 224 (5), pp. 1933-1946. https://doi.org/10.1007/s00429-019-01885-xBuilding a reduced dictionary of relevant perfusion patterns from CEUS data for the classification of testis lesions
Favaron, T., Huang, D.Y., Christensen-Jeffries, K., Eckersley, R., Sidhu, P.S. and Grisan, E. (2019). Building a reduced dictionary of relevant perfusion patterns from CEUS data for the classification of testis lesions. 2019 IEEE 16th International Symposium on Biomedical Imaging. Venice, Italy 08 - 11 Apr 2019 Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/ISBI.2019.8759528Deep Convolutional Neural Network for Survival Estimation of Amyotrophic Lateral Sclerosis patients
Grisan, E., Zandon`a, A. and Di Camillo, B. (2019). Deep Convolutional Neural Network for Survival Estimation of Amyotrophic Lateral Sclerosis patients. European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. Bruges, Belgium 24 - 26 Apr 2019 i6doc.Prediction of Adverse Glycemic Events from Continuous Glucose Monitoring Signal
Gadaleta, M., Facchinetti, A., Grisan, E. and Rossi, M. (2019). Prediction of Adverse Glycemic Events from Continuous Glucose Monitoring Signal. IEEE Journal of Biomedical and Health Informatics. 23 (2). https://doi.org/10.1109/JBHI.2018.2823763Sparse Image Reconstruction for Contrast Enhanced Cardiac Ultrasound using Diverging Waves
Stanziola, A., Toulemonde, M., Papadopoulou, V., Corbett, R., Duncan, N., Grisan, E. and Tang, M-X. (2019). Sparse Image Reconstruction for Contrast Enhanced Cardiac Ultrasound using Diverging Waves. IEEE International Ultrasonics Symposium 2019. Glasgow 09 2009 - 06 Oct 2019 Institute of Electrical and Electronics Engineers (IEEE).Super resolution ultrasound image filtering with machine learning to reduce the localization error
Harput, S., Fong, L.H., Stanziola, A., Zhang, G., Toulemonde, M., Zhou, J., Christensen-Jeffries, K., Brown, J., Eckersley, R., Grisan, E., Dunsby, C. and Tang, M. (2019). Super resolution ultrasound image filtering with machine learning to reduce the localization error. IEEE International Ultrasonics Symposium 2019. Glasgow 09 2009 - 06 Oct 2019 Institute of Electrical and Electronics Engineers (IEEE).Temporal Convolution Networks for Real-Time Abdominal Fetal Aorta Analysis with Ultrasound
Savioli, N., Visentin, S., Cosmi, E., Grisan, E., Lamata, P. and Montana, G. (2018). Temporal Convolution Networks for Real-Time Abdominal Fetal Aorta Analysis with Ultrasound. Artificial Neural Networks and Machine Learning – ICANN 2018. Rhodes, Greece 04 - 07 Oct 2018 Springer. https://doi.org/10.1007/978-3-030-01421-6_15Quantitative imaging by pixel-based contrast-enhanced ultrasound reveals a linear relationship between synovial vascular perfusion and the recruitment of pathogenic IL-17A-F+IL-23+ CD161+ CD4+ T helper cells in psoriatic arthritis joints
Fiocco, U, Stramare, R, Martini, V, Coran, A, Caso, F, Costa, L, Felicetti, M, Rizzo, G, Tonietto, M, Scanu, A, Oliviero, F, Raffeiner, B, Vezzù, M, Lunardi, F, Scarpa, R, Sacerdoti, D, Rubaltelli, L, Punzi, L, Doria, A and Grisan, E (2017). Quantitative imaging by pixel-based contrast-enhanced ultrasound reveals a linear relationship between synovial vascular perfusion and the recruitment of pathogenic IL-17A-F+IL-23+ CD161+ CD4+ T helper cells in psoriatic arthritis joints. Clinical Rheumatology. 36 (2), pp. 391-399. https://doi.org/10.1007/s10067-016-3500-xBoosting the Battery Life of Wearables for Health Monitoring Through the Compression of Biosignals
Hooshmand, M, Zordan, D, Del Testa, D, Grisan, E and Rossi, M (2017). Boosting the Battery Life of Wearables for Health Monitoring Through the Compression of Biosignals. IEEE Internet of Things Journal. 4, pp. 1647-1662. https://doi.org/10.1109/JIOT.2017.2689164Detection of a slow-flow component in contrast-enhanced ultrasound of the synovia for the differential diagnosis of arthritis
Rizzo, G, Tonietto, M, Castellaro, M, Raffeiner, B, Coran, A, Fiocco, U, Stramare, R and Grisan, E (2017). Detection of a slow-flow component in contrast-enhanced ultrasound of the synovia for the differential diagnosis of arthritis. SPIE Medical Imaging. Orlando, FL, USA 11 - 16 Feb 2017 SPIE. https://doi.org/10.1117/12.2250818Improving the quantification of contrast enhanced ultrasound using a Bayesian approach
Rizzo, G, Tonietto, M, Castellaro, M, Raffeiner, B, Coran, A, Fiocco, U, Stramare, R and Grisan, E (2017). Improving the quantification of contrast enhanced ultrasound using a Bayesian approach. SPIE Medical Imaging. Orlando, FL , USA 16 2016 - 11 Feb 2017 SPIE. https://doi.org/10.1117/12.2250195Superpixel-based classification of gastric chromoendoscopy images
Boschetto, D and Grisan, E (2017). Superpixel-based classification of gastric chromoendoscopy images. SPIE Medical Imaging. Orlando, FL, USA 11 - 16 Feb 2017 SPIE. https://doi.org/10.1117/12.2254187Boosted learned kernels for data-driven vesselness measure
Grisan, E (2017). Boosted learned kernels for data-driven vesselness measure. Proceedings Volume 10137, Medical Imaging 2017: Biomedical Applications in Molecular, Structural, and Functional Imaging; 101370Z (2017). Orlando, FL, USA 11 - 16 Feb 2017 SPIE. https://doi.org/10.1117/12.2250370Cortical Thickness variability in Multiple Sclerosis: The role of lesion segmentation and filling
Palombit, A, Castellaro, M, Calabrese, M, Romualdi, C, Pizzini, FB, Montemezzi, S, Grisan, E and Bertoldo, A (2017). Cortical Thickness variability in Multiple Sclerosis: The role of lesion segmentation and filling. 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017). Melbourne, VIC, Australia 18 - 21 Apr 2017 pp. 792-795 https://doi.org/10.1109/ISBI.2017.7950637From macro to nano: Linking quantitative CEUS perfusion parameters to CD4+ T cells subtypes in spondyloarthtitis
Grisan, E, Rizzo, G, Tonietto, M, Coran, A, Raffeiner, B, Scanu, A, Martini, V, Stramare, R and Fiocco, U (2017). From macro to nano: Linking quantitative CEUS perfusion parameters to CD4+ T cells subtypes in spondyloarthtitis. 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017). Melbourne, VIC, Australia 17 - 21 Apr 2017 Institute of Electrical and Electronics Engineers (IEEE). pp. 899-902 https://doi.org/10.1109/ISBI.2017.7950661Grade and location of power doppler are predictive of damage progression in rheumatoid arthritis patients in clinical remission by anti-tumour necrosis factor α
Raffeiner, B, Grisan, E, Botsios, C, Stramare, R, Rizzo, G, Bernardi, L, Punzi, L, Ometto, F and Doria, A (2017). Grade and location of power doppler are predictive of damage progression in rheumatoid arthritis patients in clinical remission by anti-tumour necrosis factor α. Rheumatology (United Kingdom). 56, pp. 1320-1325. https://doi.org/10.1093/rheumatology/kex084