A shape-constraint adversarial framework with instance-normalized spatio-temporal features for inter-fetal membrane segmentation
Alessandro Casella,Alessandro Casella,Sara Moccia,Dario Paladini,Emanuele Frontoni,Elena De Momi,Leonardo S. Mattos +6 more
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TLDR
In this paper, a new deep learning framework for inter-fetal membrane segmentation on in-vivo fetoscopic videos is presented, which enhances existing architectures by encoding a novel (instance-normalized) dense block, invariant to illumination changes, that extracts spatio-temporal features to enforce pixel connectivity in time, and relying on an adversarial training, which constrains macro appearance.About:
This article is published in Medical Image Analysis.The article was published on 2021-02-19 and is currently open access. It has received 9 citations till now.read more
Citations
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Journal ArticleDOI
A Review on Deep-Learning Algorithms for Fetal Ultrasound-Image Analysis
Maria Chiara Fiorentino,Francesca Pia Villani,Mariachiara Di Cosmo,Emanuele Frontoni,Sara Moccia +4 more
TL;DR: A detailed survey of the most recent work in the field can be found in this paper , with a total of 145 research papers published after 2017 and each paper is analyzed and commented on from both the methodology and application perspective.
Journal ArticleDOI
Artificial intelligence in the diagnosis of necrotising enterocolitis in newborns
Arkadiusz Sitek,Joanna Seliga-Siwecka,Szymon Płotka,Michał K. Grzeszczyk,Szymon Seliga,Krzysztof Wlodarczyk,Renata Bokiniec +6 more
TL;DR: A literature search on the use of AI in the diagnosis of NEC yielded 118 publications that were reduced to 8 after screening and checking for eligibility, and most publications showed promising results but no publications with evident clinical benefits were found.
Journal ArticleDOI
A deep learning approach to median nerve evaluation in ultrasound images of carpal tunnel inlet
Mariachiara Di Cosmo,Maria Chiara Fiorentino,Francesca Pia Villani,Emanuele Frontoni,Gianluca Smerilli,Emilio Filippucci,Sara Moccia +6 more
TL;DR: Wang et al. as discussed by the authors used Mask R-CNN with two additional transposed layers at segmentation head to accurately segment the median nerve directly on transverse US images, which achieved good performances both in median nerve detection and segmentation: Precision (Prec), Recall (Rec), Mean Average Precision (mAP) and Dice Similarity Coefficient (DSC).
Journal ArticleDOI
FUN-SIS: a Fully UNsupervised approach for Surgical Instrument Segmentation
TL;DR: In this paper , a fully-unsupervised approach for binary Surgical Instrument Segmentation is proposed, which uses shape-priors as realistic segmentation masks of the instruments, not necessarily coming from the same dataset/domain as the videos.
Journal ArticleDOI
Computer‐assisted fetal laser surgery in the treatment of twin‐to‐twin transfusion syndrome: Recent trends and prospects
TL;DR: This review uncovers the literature on computer‐assisted software solutions focused on TTTS and evaluates the current maturity of technologies by the technology readiness level and enumerates the necessary aspects to bring these new technologies to clinical practice.
References
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Proceedings ArticleDOI
Real-time mosaicing of fetoscopic videos using SIFT
Pankaj Daga,Francois Chadebecq,Dzhoshkun I. Shakir,Luis Carlos Garcia-Peraza Herrera,Marcel Tella,George Dwyer,Anna L. David,Jan Deprest,Danail Stoyanov,Tom Vercauteren,Sebastien Ourselin +10 more
TL;DR: Initial qualitative results on ex-vivo placental images indicate that the proposed framework can generate clinically useful mosaics from fetoscopic videos in real-time, and leverages the parallelism of modern GPUs and can process clinical fetoscopic images inreal-time.
Book ChapterDOI
MuTGAN: Simultaneous Segmentation and Quantification of Myocardial Infarction Without Contrast Agents via Joint Adversarial Learning.
TL;DR: The proposed MuTGAN method yielded a pixel classification accuracy of 96.46%, and the mean absolute error of the MI centroid was 0.977 mm, from 140 clinical subjects, indicating the potential of the proposed method in aiding standardized MI assessments.
Journal ArticleDOI
Stable Image Registration for In-Vivo Fetoscopic Panorama Reconstruction
TL;DR: A system can be developed that supports the surgeon during the surgery, by giving feedback and providing a more complete overview of the placenta, by proposing a stable region detection method as well as extracting matchable features based on a deep-learning approach.
Journal ArticleDOI
Inter-foetus Membrane Segmentation for TTTS Using Adversarial Networks
Alessandro Casella,Alessandro Casella,Sara Moccia,Sara Moccia,Emanuele Frontoni,Dario Paladini,Elena De Momi,Leonardo S. Mattos +7 more
TL;DR: An adversarial network consisting of two Fully-Convolutional Neural Networks that could be a valuable and robust solution to assist surgeons in providing membrane identification while performing fetoscopy.
Journal ArticleDOI
Retrieval and registration of long-range overlapping frames for scalable mosaicking of in vivo fetoscopy.
Loïc Peter,Marcel Tella-Amo,Dzhoshkun I. Shakir,George Attilakos,Ruwan Wimalasundera,Jan Deprest,Jan Deprest,Sebastien Ourselin,Tom Vercauteren,Tom Vercauteren +9 more
TL;DR: This paper proposes the first approach for the construction of mosaics of placenta in in vivo fetoscopy sequences, offering first positive results on in vivo data for which standard mosaicking techniques are not applicable.