Výsledky vyhledávání - "Andrea Guerriero"

Akademický článek

A neural network for glomerulus classification based on histological images of kidney biopsy

Autor: Giacomo Donato Cascarano, Francesco Saverio Debitonto, Ruggero Lemma, Antonio Brunetti, Domenico Buongiorno, Irio De Feudis, Andrea Guerriero, Umberto Venere, Silvia Matino, Maria Teresa Rocchetti, Michele Rossini, Francesco Pesce, Loreto Gesualdo, Vitoantonio Bevilacqua

Publikováno v: BMC Medical Informatics and Decision Making, Vol 21, Iss S1, Pp 1-14 (2021)

Abstract Background Computer-aided diagnosis (CAD) systems based on medical images could support physicians in the decision-making process. During the last decades, researchers have proposed CAD systems in several medical domains achieving promising

Externí odkaz: https://doaj.org/article/db873284506541638164c996738de283

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Akademický článek

A comparison between two semantic deep learning frameworks for the autosomal dominant polycystic kidney disease segmentation based on magnetic resonance images

Autor: Vitoantonio Bevilacqua, Antonio Brunetti, Giacomo Donato Cascarano, Andrea Guerriero, Francesco Pesce, Marco Moschetta, Loreto Gesualdo

Publikováno v: BMC Medical Informatics and Decision Making, Vol 19, Iss S9, Pp 1-12 (2019)

Abstract Background The automatic segmentation of kidneys in medical images is not a trivial task when the subjects undergoing the medical examination are affected by Autosomal Dominant Polycystic Kidney Disease (ADPKD). Several works dealing with th

Externí odkaz: https://doaj.org/article/cde01aa55ff94b84bb5d1c3c81c5a8cd

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Akademický článek

Focal Dice Loss-Based V-Net for Liver Segments Classification

Autor: Berardino Prencipe, Nicola Altini, Giacomo Donato Cascarano, Antonio Brunetti, Andrea Guerriero, Vitoantonio Bevilacqua

Publikováno v: Applied Sciences, Vol 12, Iss 7, p 3247 (2022)

Liver segmentation is a crucial step in surgical planning from computed tomography scans. The possibility to obtain a precise delineation of the liver boundaries with the exploitation of automatic techniques can help the radiologists, reducing the an

Externí odkaz: https://doaj.org/article/5066c03f64c242cb9b73171989f0db46

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Akademický článek

Segmentation and Identification of Vertebrae in CT Scans Using CNN, k-Means Clustering and k-NN

Autor: Nicola Altini, Giuseppe De Giosa, Nicola Fragasso, Claudia Coscia, Elena Sibilano, Berardino Prencipe, Sardar Mehboob Hussain, Antonio Brunetti, Domenico Buongiorno, Andrea Guerriero, Ilaria Sabina Tatò, Gioacchino Brunetti, Vito Triggiani, Vitoantonio Bevilacqua

Publikováno v: Informatics, Vol 8, Iss 2, p 40 (2021)

The accurate segmentation and identification of vertebrae presents the foundations for spine analysis including fractures, malfunctions and other visual insights. The large-scale vertebrae segmentation challenge (VerSe), organized as a competition at

Externí odkaz: https://doaj.org/article/c04e2ec5a8e940fca761c0f9e91f0d26

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A Tversky Loss-Based Convolutional Neural Network for Liver Vessels Segmentation

Autor: Arnaldo Scardapane, Vito Triggiani, Francescomaria Marino, Antonio Brunetti, Andrea Guerriero, Gioacchino Brunetti, Leonarda Carnimeo, Laura Villani, Berardino Prencipe, Nicola Altini, Giacomo Donato Cascarano

Publikováno v: Intelligent Computing Theories and Application ISBN: 9783030607982
ICIC (1)

The volumetric estimation of organs is a crucial issue both for the diagnosis or assessment of pathologies and for surgical planning. Three-dimensional imaging techniques, e.g. Computed Tomography (CT), are widely used for this task, allowing to perf

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cc26266c684594de675bc9c96c24945f
https://doi.org/10.1007/978-3-030-60799-9_30

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A Novel Approach Based on Region Growing Algorithm for Liver and Spleen Segmentation from CT Scans

Autor: Antonio Brunetti, Berardino Prencipe, Nicola Altini, Andrea Guerriero, Giacomo Donato Cascarano

Publikováno v: Intelligent Computing Theories and Application ISBN: 9783030607982
ICIC (1)

In this paper, we propose a novel approach to adapt 2D region growing algorithms to volumetric segmentation of liver and spleen from Computed Tomography (CT) scans. Abdominal organ segmentation is an essential and time-consuming task in clinical radi

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::16b10919c5f2453568c58150f867a9a7
https://doi.org/10.1007/978-3-030-60799-9_35

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A comparison between two semantic deep learning frameworks for the autosomal dominant polycystic kidney disease segmentation based on magnetic resonance images

Autor: Andrea Guerriero, Francesco Pesce, Vitoantonio Bevilacqua, Antonio Brunetti, Loreto Gesualdo, Giacomo Donato Cascarano, Marco Moschetta

Publikováno v: BMC Medical Informatics and Decision Making
BMC Medical Informatics and Decision Making, Vol 19, Iss S9, Pp 1-12 (2019)

BackgroundThe automatic segmentation of kidneys in medical images is not a trivial task when the subjects undergoing the medical examination are affected by Autosomal Dominant Polycystic Kidney Disease (ADPKD). Several works dealing with the segmenta

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f96309c1c0e575305ccc26a2f856c04f
https://doi.org/10.1186/s12911-019-0988-4

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Characterization of adrenal lesions using MDCT wash-out parameters: diagnostic accuracy of several combinations of intermediate and delayed phases

Autor: Niccolò Faccioli, Giovanni Carbognin, Lino Furlani, Giovanni Foti, Giuseppe Malleo, Andrea Guerriero

Publikováno v: La radiologia medica. 123:833-840

To evaluate the diagnostic accuracy of wash-out parameters calculated using multiple intermediate and delayed phases. This prospective study had institutional review board approval and informed consent was obtained from all patients. Between January

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c02b7897fb9048e74e6defd3fc5530bb
https://doi.org/10.1007/s11547-018-0911-6

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A performance comparison between shallow and deeper neural networks supervised classification of tomosynthesis breast lesions images

Autor: Antonio Brunetti, Michele Telegrafo, Andrea Guerriero, Marco Moschetta, Vitoantonio Bevilacqua, Gianpaolo Francesco Trotta

Computer Aided Decision (CAD) systems, based on 3D tomosynthesis imaging, could support radiologists in classifying different kinds of breast lesions and then improve the diagnosis of breast cancer (BC) with a lower X-ray dose than in Computer Tomogr

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::23df7375ddc90154158c4cc93d96fa8b
http://hdl.handle.net/11589/159988

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