Sara Moccia

Affiliated Researcher
Affiliated Researcher

Contacts

Via Morego, 30, Genova, 16163, Italy.

Social profiles

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About

Sara Moccia  (B.Sc. 2012, M.Sc. 2014, Ph.D. 2018) was born in Bari on September 1990. She graduated cum laude in Biomedical Engineering at Politecnico di Milano in December 2014, with a thesis entitled: "Statistical segmentation techniques of liver metastases and necroses in FGD-PET for the automatic evaluation of pre and post thermo ablation PET/CT studies". 

She obtained the European PhD cum laude in Bioengineering from Istituto Italiano di Tecnologia (Genoa, Italy) and Politecnico di Milano (Milano, Italy) with a thesis entitled "Supervised tissue classification in optical images: Towards new applications of surgical data science". During her PhD, she was hosted at the Computer-Assisted Medical Interventions laboratory at the DKFZ in Heidelberg (Germany).

Sara is currently a Postdoc at Università Politecnica delle Marche (Ancona, Italy) and Affiliated Researcher at Istituto Italiano di Tecnologia (Genoa, Italy).

Her research is mainly focused on intra-operative optical-image analysis, exploiting machine-learning and deep-learning methodologies to provide robust and reliable tissue classification.

Interests

Medical-image analysis Machine learning Surgical data science Deep learning Computer-assisted diagnosis

IIT Publications

  • 2021
  • Fiorentino M.C., Moccia S.iit, Capparuccini M., Giamberini S., Frontoni E.
    DOI

    A regression framework to head-circumference delineation from US fetal images

    Computer Methods and Programs in Biomedicine, vol. 198
  • 2020
  • Zaffino P., Moccia S., De Momi E., Spadea M.F.
    DOI

    A Review on Advances in Intra-operative Imaging for Surgery and Therapy: Imagining the Operating Room of the Future

    Annals of Biomedical Engineering, vol. 48, (no. 8), pp. 2171-2191
  • Berardini D., Migliorelli L., Moccia S., Naldini M., Angelis G.D., Frontoni E.
    DOI

    Evaluating the autonomy of children with autism spectrum disorder in washing hands: A deep-learning approach

    Proceedings - International Symposium on Computers and Communications, vol. 2020-July
  • Antognoli L., Moccia S.iit, Migliorelli L., Casaccia S., Scalise L., Frontoni E.
    DOI

    Heartbeat detection by laser doppler vibrometry and machine learning

    Sensors, vol. 20, (no. 18), pp. 1-18
  • Casella A.iit, Moccia S.iit, Frontoni E., Paladini D., De Momi E., Mattos L.S.iit
    DOI

    Inter-foetus Membrane Segmentation for TTTS Using Adversarial Networks

    Annals of Biomedical Engineering, vol. 48, (no. 2), pp. 848-859
  • Moccia S.iit, Migliorelli L., Carnielli V., Frontoni E.
    DOI

    Preterm Infants' Pose Estimation with Spatio-Temporal Features

    IEEE Transactions on Biomedical Engineering, vol. 67, (no. 8), pp. 2370-2380
  • Moccia S.iit, Romeo L.iit, Migliorelli L., Frontoni E., Zingaretti P.
    DOI

    Supervised cnn strategies for optical image segmentation and classification in interventional medicine

    Intelligent Systems Reference Library, vol. 186, pp. 213-236
  • Migliorelli L., Moccia S.iit, Pietrini R., Carnielli V.P., Frontoni E.
    DOI

    The babyPose dataset

    Data in Brief, vol. 33
  • Patrini I., Ruperti M., Moccia S.iit, Mattos L.S.iit, Frontoni E., De Momi E.
    DOI

    Transfer learning for informative-frame selection in laryngoscopic videos through learned features

    Medical and Biological Engineering and Computing, vol. 58, (no. 6), pp. 1225-1238
  • Cesaretti M.iit, Brustia R., Goumard C., Cauchy F., Pote N., Dondero F., Paugam-Burtz C., Durand F., Paradis V., Diaspro A.iit, Mattos L.iit, Scatton O., Soubrane O., Moccia S.iit
    DOI

    Use of Artificial Intelligence as an Innovative Method for Liver Graft Macrosteatosis Assessment

    Liver Transplantation, vol. 26, (no. 10), pp. 1224-1232
  • 2019
  • Migliorelli L., Cenci A., Bernardini M., Romeo L., Moccia S., Zingaretti P.
    DOI

    A cloud-based healthcare infrastructure for neonatal intensive-care units

    Proceedings of the ASME Design Engineering Technical Conference, vol. 9
  • Patrini I., Ruperti M., De Momi E., Mattos L. S.iit, Frontoni E., Moccia S.iit

    A deep-learning strategy for informative-frame selection and early-stage cancer diagnosis in laryngoscopic videos

    9th CRAS + 30th SPIGC joint conference
  • Fiorentino M.C., Moccia S.iit, Cipolletta E., Filippucci E., Frontoni E.
    DOI

    A Learning Approach for Informative-Frame Selection in US Rheumatology Images

    Lecture Notes in Computer Science, vol. 11808 LNCS, pp. 228-236
  • Bernardini M., Ferri A., Migliorelli L., Moccia S., Romeo L., Silvestri S., Tiano L., Mancini A.
    DOI

    Augmented microscopy for DNA damage quantification: A machine learning tool for environmental, medical and health sciences

    Proceedings of the ASME Design Engineering Technical Conference, vol. 9
  • Ambrosini E., Caielli M., Milis M., Loizou C., Azzolino D., Damanti S., Bertagnoli L., Cesari M., Moccia S., Cid M., De Isla C.G., Salamanca P., Borghese N.A., Ferrante S.
    DOI

    Automatic speech analysis to early detect functional cognitive decline in elderly population

    Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings, pp. 212-216
  • Hadji S.E., Moccia S.iit, Scorza D., Rizzi M., Cardinale F., Baselli G., Momi E.D.
    DOI

    Brain-vascular segmentation for SEEG planning via a 3D fully-convolutional neural network

    Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings, pp. 1014-1017
  • Colleoni E., Moccia S.iit, Du X., De Momi E., Stoyanov D.
    DOI

    Deep Learning Based Robotic Tool Detection and Articulation Estimation with Spatio-Temporal Layers

    IEEE Robotics and Automation Letters, vol. 4, (no. 3), pp. 2714-2721
  • Moccia S.iit, Banali R., Martini C., Muscogiuri G., Pontone G., Pepi M., Caiani E.G.
    DOI

    Development and testing of a deep learning-based strategy for scar segmentation on CMR-LGE images

    Magnetic Resonance Materials in Physics, Biology, and Medicine, vol. 32, (no. 2), pp. 187-195
  • Penza V.iit, Moccia S.iit, De Momi E., Mattos L.iit

    Enhanced Vision to improve Safety in Robotic Surgery

    Elsevier Handbook of Robotic and Image-Guided Surgery, Publisher: Elsevier
  • Vidotto M., De Momi E., Gazzara M., Mattos L.S.iit, Ferrigno G., Moccia S.iit
    DOI

    FCNN-based axon segmentation for convection-enhanced delivery optimization

    Computer-Assisted Radiology and Surgery, vol. 14, (no. 3), pp. 493-499
  • Cesaretti M.iit, Zarzavajian Le Bian A., Moccia S.iit, Iannelli A., Schiavo L., Diaspro A.iit
    DOI

    From deceased to bioengineered graft: New frontiers in liver transplantation

    Transplantation Reviews, vol. 33, (no. 2), pp. 72-76
  • Araujo T., Santos C.P., De Momi E., Moccia S.iit
    DOI

    Learned and handcrafted features for early-stage laryngeal SCC diagnosis

    Medical and Biological Engineering and Computing, vol. 57, (no. 12), pp. 2683-2692
  • Calamanti C., Moccia S., Migliorelli L., Paolanti M., Frontoni E.
    DOI

    Learning-based screening of endothelial dysfunction from photoplethysmographic signals

    Electronics (Switzerland), vol. 8, (no. 3)
  • Migliorelli L., Moccia S., Avellino I., Fiorentino M.C., Frontoni E.
    DOI

    MyDi application: Towards automatic activity annotation of young patients with Type 1 diabetes

    2019 IEEE 23rd International Symposium on Consumer Technologies, ISCT 2019, pp. 220-224
  • Moccia S.iit, Migliorelli L.iit, Pietrini R.iit, Frontoni E.iit
    DOI

    Preterm infants' limb-pose estimation from depth images using convolutional neural networks

    2019 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2019
  • Casella A., Paladini D., De Momi E., Mattos L. S.iit, Moccia S.iit

    Residual networks for inter-foetus membrane segmentation in fetoscopy

    9th CRAS + 30th SPIGC joint conference
  • Frontoni E., Mancini A., Baldi M., Paolanti M., Moccia S., Zingaretti P., Landro V., Misericordia P.
    DOI

    Sharing health data among general practitioners: The Nu.Sa. project

    International Journal of Medical Informatics, vol. 129, pp. 267-274
  • 2018
  • Moccia S.iit, Banali R., Martini C., Moscogiuri G., Pontone G., Pepi M., Caiani E.G.
    DOI

    Automated Scar Segmentation from CMR-LGE Images Using a Deep Learning Approach

    Computing in Cardiology, vol. 2018-September
  • Moccia S.iit, De Momi E., El Hadji S., Mattos L.S.iit
    DOI

    Blood vessel segmentation algorithms — Review of methods, datasets and evaluation metrics

    Computer Methods and Programs in Biomedicine, vol. 158, pp. 71-91
  • Moccia S.iit, Mattos L.S.iit, Patrini I., Ruperti M., Pote N., Dondero F., Cauchy F., Sepulveda A., Soubrane O., De Momi E., Diaspro A.iit, Cesaretti M.iit
    DOI

    Computer-assisted liver graft steatosis assessment via learning-based texture analysis

    Computer-Assisted Radiology and Surgery, vol. 13, (no. 9), pp. 1357-1367
  • Penza V.iit, Moccia S.iit, Gallarello A., Panaccio A., De Momi E., Mattos L. S.iit

    Context-Aware Augmented Reality for Laparoscopy

    Sixth National Congress of Bioengineering
  • Penza V.iit, Ciullo A.S., Moccia S.iit, Mattos L.S.iit, De Momi E.
    DOI

    EndoAbS dataset: Endoscopic abdominal stereo image dataset for benchmarking 3D stereo reconstruction algorithms

    International Journal of Medical Robotics and Computer Assisted Surgery, vol. 14, (no. 5)
  • Penza V.iit, Moccia S.iit, De Momi E., Mattos L. S.iit

    Enhanced Vision to improve Safety in Robotic Surgery

    Elsevier Handbook of Robotic and Image-Guided Surgery
  • Gazzara M., Vidotto M., Mattos L.iit, Ferrigno G., De Momi E., Moccia S.iit

    FCNN-based axon segmentation for convection-enhanced delivery optimization

    International Congress and Exhibition on Computer Assisted Radiology and Surgery
  • Moccia S.iit, Vanone G.O., Momi E.D., Laborai A., Guastini L., Peretti G., Mattos L.S.iit
    DOI

    Learning-based classification of informative laryngoscopic frames

    Computer Methods and Programs in Biomedicine, vol. 158, pp. 21-30
  • Moccia S.iit, Patrini I., Ruperti M., De Momi E., Diaspro A.iit, Soubrane O., Mattos L.iit, Cesaretti M.

    Liver-donor steatosis assessment from smartphone images acquired in the OR

    Congresso Gruppo Nazionale di Bioingegneria
  • Moccia S.iit, Foti S., Routray A., Prudente F., Perin A., Sekula R.F., Mattos L.S.iit, Balzer J.R., Fellows-Mayle W., De Momi E., Riviere C.N.
    DOI

    Toward Improving Safety in Neurosurgery with an Active Handheld Instrument

    Annals of Biomedical Engineering, vol. 46, (no. 10), pp. 1450-1464
  • Morelli A., Moccia S.iit, Mattos L.iit, Cordima G., De Cobelli O., Ferrigno G., De Momi E.

    Towards deformable registration for AR in nephrectomy

    Congresso Gruppo Nazionale di Bioingegneria
  • Moccia S.iit, Wirkert S.J., Kenngott H., Vemuri A.S., Apitz M., Mayer B., De Momi E., Mattos L.S.iit, Maier-Hein L.
    DOI

    Uncertainty-aware organ classification for surgical data science applications in laparoscopy

    IEEE Transactions on Biomedical Engineering, vol. 65, (no. 11), pp. 2649-2659
  • 2017
  • Moccia S.iit, De Momi E., Guarnaschelli M., Savazzi M., Laborai A., Guastini L., Peretti G., Mattos L.S.iit
    DOI

    Confident texture-based laryngeal tissue classification for early stage diagnosis support

    Journal of Medical Imaging, vol. 4, (no. 3)
  • Penza V., Ciullo A.iit, Moccia S.iit, Mattos L.iit, De Momi E.

    EndoAbS Dataset: Endoscopic Abdominal Stereo Image Dataset for Benchmarking 3D Stereo Reconstruction Algorithms

    International Journal of Medical Robotics and Computer Assisted Surgery
  • Wirkert S.J., Vemuri A.S., Kenngott H.G., Moccia S.iit, Gotz M., Mayer B.F.B., Maier-Hein K.H., Elson D.S., Maier-Hein L.
    DOI

    Physiological parameter estimation from multispectral images unleashed

    Lecture Notes in Computer Science, vol. 10435 LNCS, pp. 134-141
  • Scorza D., Moccia S.iit, De Luca G., Plaino L., Cardinale F., Mattos L.S.iit, Kabongo L., De Momi E.
    DOI

    Safe electrode trajectory planning in SEEG via MIP-based vessel segmentation

    Progress in Biomedical Optics and Imaging - Proceedings of SPIE, vol. 10135
  • Prudente F., Moccia S.iit, Perin A., Sekula R. F., Mattos L.iit, Balzer J. R., Fellows-Mayle W., De Momi E., Riviere C.

    Toward safer neurosurgery with an active handheld instrument

    The Hamlyn Symposium on Medical Robotics
  • Prudente F., Moccia S.iit, Perin A., Sekula R. F., Mattos L.iit, Balzer J. R., Fellows-Mayle W., De Momi E., Riviere C.

    Toward safer neurosurgery with an active handheld instrument,” Hamlyn Symposium on Medical Robotics

    The Hamlyn Symposium on Medical Robotics
  • 2016
  • Moccia S.iit, Penza V.iit, Vanone G.O., De Momi E., Mattos L.S.iit
    DOI

    Automatic workflow for narrow-band laryngeal video stitching

    Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings, vol. 2016-October, pp. 1188-1191
  • 2015
  • Moccia S.iit, Baselli G., De Momi E., Mattos L.iit

    Vocal Folds Disorders Detection and Classification in Endoscopic Narrow-Band Images

    5th Joint Workshop on New Technologies for Computer/Robot Assisted Surgery

Awards