Výsledky vyhledávání - "Fausto Milletari"

Towards an AI-based assessment model of surgical difficulty during early phase laparoscopic cholecystectomy

Autor: Julian. R. Abbing, Frank J. Voskens, Beerend G. A. Gerats, Ruby M. Egging, Fausto Milletari, Ivo A.M.J. Broeders

Publikováno v: Computer Methods in Biomechanics and Biomedical Engineering: Imaging and Visualization. Taylor & Francis

Laparoscopic cholecystectomy (LC) is the standard surgical treatment for patients with gallstone disease, ranging from symptomatic cholelithiasis to severe cholecystitis. As there is high variability in operative findings during LC, it is important t

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::867b2754b45b489134d361482dbfd1e0
https://research.utwente.nl/en/publications/385e06c6-eed1-4ccb-b2e8-9938fcf6a715

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Automatic classification of dopamine transporter SPECT: deep convolutional neural networks can be trained to be robust with respect to variable image characteristics

Autor: Markus Wenzel, Susanne Klutmann, Ivayla Apostolova, Fausto Milletari, Ralph Buchert, Catharina Lange, Marcus Ehrenburg, Michael Schenk, Julia Krüger

Publikováno v: European Journal of Nuclear Medicine and Molecular Imaging. 46:2800-2811

This study investigated the potential of deep convolutional neural networks (CNN) for automatic classification of FP-CIT SPECT in multi-site or multi-camera settings with variable image characteristics. The study included FP-CIT SPECT of 645 subjects

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fd79e7fee0344fb15eebce8790496384
https://doi.org/10.1007/s00259-019-04502-5

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Cloud Deployment of High-Resolution Medical Image Analysis With TOMAAT

Autor: Fausto Milletari, Gerome Vivar, Moustafa Aboulatta, Seyed-Ahmad Ahmadi, Johann Frei

Publikováno v: IEEE Journal of Biomedical and Health Informatics. 23:969-977

Background: Deep learning has been recently applied to a multitude of computer vision and medical image analysis problems. Although recent research efforts have improved the state of the art, most of the methods cannot be easily accessed, compared or

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5ad1b67727127d54919db7adac62a92c
https://doi.org/10.1109/jbhi.2018.2885214

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Robust navigation support in lowest dose image setting

Autor: Mai Bui, Felix Bourier, Christoph Baur, Nassir Navab, Fausto Milletari, Stefanie Demirci

Publikováno v: International Journal of Computer Assisted Radiology and Surgery. 14:291-300

Clinical cardiac electrophysiology (EP) is concerned with diagnosis and treatment of cardiac arrhythmia describing abnormality or perturbation in the normal activation sequence of the myocardium. With the recent introduction of lowest dose X-ray imag

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::309727d03722d8bb778ada5a40b9f480
https://doi.org/10.1007/s11548-018-1874-8

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Hough-CNN: Deep learning for segmentation of deep brain regions in MRI and ultrasound

Autor: Verena E. Rozanski, Birgit Ertl-Wagner, Fausto Milletari, Kai Bötzel, Johannes Levin, Annika Plate, Juliana Maiostre, Seyed-Ahmad Ahmadi, Olaf Dietrich, Christine Kroll, Nassir Navab

Publikováno v: Computer Vision and Image Understanding. 164:92-102

In this work we propose a novel approach to perform segmentation by leveraging the abstraction capabilities of convolutional neural networks (CNNs). Our method is based on Hough voting, a strategy that allows for fully automatic localisation and segm

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::625ed92cc5b3468d6383b50bc1122689
https://doi.org/10.1016/j.cviu.2017.04.002

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3D intra-operative ultrasound and MR image guidance: pursuing an ultrasound-based management of brainshift to enhance neuronavigation

Autor: Lorenzo Bello, Federico Pessina, Fausto Milletari, Benjamín Gutiérrez-Becker, Nassir Navab, Antonella Castellano, Amin Katouzian, Christoph Hennersperger, Marco Riva

Publikováno v: International Journal of Computer Assisted Radiology and Surgery

Brainshift is still a major issue in neuronavigation. Incorporating intra-operative ultrasound (iUS) with advanced registration algorithms within the surgical workflow is regarded as a promising approach for a better understanding and management of b

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3a943d95523e821a85f071821879d421
https://doi.org/10.1007/s11548-017-1578-5

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Privacy-Preserving Federated Brain Tumour Segmentation

Autor: Fausto Milletari, Wenqi Li, Sebastien Ourselin, Wentao Zhu, Andrew Feng, Jonny Hancox, M. Jorge Cardoso, Daguang Xu, Nicola Rieke, Yan Cheng, Maximilian Baust

Publikováno v: Machine Learning in Medical Imaging ISBN: 9783030326913
MLMI@MICCAI

Due to medical data privacy regulations, it is often infeasible to collect and share patient data in a centralised data lake. This poses challenges for training machine learning algorithms, such as deep convolutional networks, which often require lar

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::1df6d4ab68706fe33eab00c8c4323a18
https://doi.org/10.1007/978-3-030-32692-0_16

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Weakly Supervised Segmentation from Extreme Points

Autor: Daguang Xu, Ling Zhang, Fausto Milletari, Holger R. Roth, Xiaosong Wang, Dong Yang, Ziyue Xu

Publikováno v: Lecture Notes in Computer Science ISBN: 9783030336417

Annotation of medical images has been a major bottleneck for the development of accurate and robust machine learning models. Annotation is costly and time-consuming and typically requires expert knowledge, especially in the medical domain. Here, we p

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::0cf4feaf4bbd5a5064fd279f3c4521d2
https://doi.org/10.1007/978-3-030-33642-4_5

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Tunable CT Lung Nodule Synthesis Conditioned on Background Image and Semantic Features

Autor: Daguang Xu, Xiaosong Wang, Ziyue Xu, Ling Zhang, Hoo-Chang Shin, Holger R. Roth, Dong Yang, Fausto Milletari

Publikováno v: Simulation and Synthesis in Medical Imaging ISBN: 9783030327774
SASHIMI@MICCAI

Synthetic CT image with artificially generated lung nodules has been shown to be useful as an augmentation method for certain tasks such as lung segmentation and nodule classification. Most conventional methods are designed as “inpainting” tasks

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::251e2cb7f5d0edfdb5089d2c75a59f22
https://doi.org/10.1007/978-3-030-32778-1_7

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Searching Learning Strategy with Reinforcement Learning for 3D Medical Image Segmentation

Autor: Dong Yang, Holger R. Roth, Fausto Milletari, Ziyue Xu, Daguang Xu, Ling Zhang

Publikováno v: Lecture Notes in Computer Science ISBN: 9783030322441
MICCAI (2)

Deep neural network (DNN) based approaches have been widely investigated and deployed in medical image analysis. For example, fully convolutional neural networks (FCN) achieve the state-of-the-art performance in several applications of 2D/3D medical

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::630fda8f30c63e0937e4e6fca1de00f8
https://doi.org/10.1007/978-3-030-32245-8_1

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