Zobrazeno 1 - 10
of 93
pro vyhledávání: '"Kristen M. Meiburger"'
Autor:
Tanweer Ali, Sameena Pathan, Massimo Salvi, Kristen M. Meiburger, Filippo Molinari, U. Rajendra Acharya
Publikováno v:
IEEE Access, Vol 12, Pp 73970-73979 (2024)
Deep learning methods have shown promise for automated medical image analysis tasks. However, class imbalance is a common challenge that can negatively impact model performance, especially for tasks with minority classes that are clinically significa
Externí odkaz:
https://doaj.org/article/1b2e81f384c74ca9a8ec76c921de86ed
Publikováno v:
IEEE Access, Vol 12, Pp 30824-30838 (2024)
Automated segmentation of histological structures in microscopy images is a crucial step in computer-aided diagnosis framework. However, this task remains a challenging problem due to issues like overlapping and touching objects, shape variation, and
Externí odkaz:
https://doaj.org/article/efd58a1939c54120975506aa547c23d9
Autor:
Francesco Branciforti, Massimo Salvi, Filippo D’Agostino, Francesco Marzola, Sara Cornacchia, Maria Olimpia De Titta, Girolamo Mastronuzzi, Isotta Meloni, Miriam Moschetta, Niccolò Porciani, Fabrizio Sciscenti, Alessandro Spertini, Andrea Spilla, Ilenia Zagaria, Abigail J. Deloria, Shiyu Deng, Richard Haindl, Gergely Szakacs, Agnes Csiszar, Mengyang Liu, Wolfgang Drexler, Filippo Molinari, Kristen M. Meiburger
Publikováno v:
Diagnostics, Vol 14, Iss 12, p 1217 (2024)
Recent years have ushered in a transformative era in in vitro modeling with the advent of organoids, three-dimensional structures derived from stem cells or patient tumor cells. Still, fully harnessing the potential of organoids requires advanced ima
Externí odkaz:
https://doaj.org/article/52644315985a447cb8bcb4d9538226ee
Autor:
Marco Carbonaro, Kristen M. Meiburger, Silvia Seoni, Emma F. Hodson-Tole, Taian Vieira, Alberto Botter
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-14 (2022)
Abstract Electromyography and ultrasonography provide complementary information about electrophysiological and physical (i.e. anatomical and mechanical) muscle properties. In this study, we propose a method to assess the electrical and physical prope
Externí odkaz:
https://doaj.org/article/e31e6a724f6741f98a2ba6a8a214fda9
Autor:
Federica Veronese, Silvia Seoni, Vanessa Tarantino, Matteo Buttafava, Chiara Airoldi, Kristen M. Meiburger, Elisa Zavattaro, Paola Savoia
Publikováno v:
Frontiers in Medicine, Vol 9 (2022)
IntroductionThe high incidence of actinic keratoses among both the elderly population and immunocompromised subjects and the considerable risk of progression from in situ to invasive neoplasms makes it essential to identify new prevention, treatment,
Externí odkaz:
https://doaj.org/article/520185386dcf4c7783510761bc18ebc2
Autor:
U. Rajendra Acharya, Kristen M. Meiburger, Joel En Wei Koh, Edward J. Ciaccio, N. Arunkumar, Mee Hoong See, Nur Aishah Mohd Taib, Anushya Vijayananthan, Kartini Rahmat, Farhana Fadzli, Sook Sam Leong, Caroline Judy Westerhout, Angela Chantre-Astaiza, Gustavo Ramirez-Gonzalez
Publikováno v:
IEEE Access, Vol 7, Pp 22829-22842 (2019)
Breast cancer is the most commonly occurring cancer in women worldwide. While mammography remains the gold standard in breast cancer screening, ultrasound is an important imaging modality for both screening and cancer diagnosis. This paper presents a
Externí odkaz:
https://doaj.org/article/c84538bfb75a4260b46efa68723f725e
Autor:
Federica Veronese, Vanessa Tarantino, Elisa Zavattaro, Francesca Biacchi, Chiara Airoldi, Massimo Salvi, Silvia Seoni, Francesco Branciforti, Kristen M. Meiburger, Paola Savoia
Publikováno v:
Diagnostics, Vol 12, Iss 6, p 1371 (2022)
Background: Due to the COVID-19 pandemic, teledermoscopy has been increasingly used in the remote diagnosis of skin cancers. In a study conducted in 2020, we demonstrated a potential role of an inexpensive device (NurugoTM Derma) as a first triage to
Externí odkaz:
https://doaj.org/article/3b09a05669c4421e948a9246bb3d2aee
Publikováno v:
Computer Methods and Programs in Biomedicine Update, Vol 1, Iss , Pp 100004- (2021)
Background: Recently, deep learning has rapidly become the methodology of choice in digital pathology image analysis. However, due to the current challenges of digital pathology (color stain variability, large images, etc.), specific pre-processing s
Externí odkaz:
https://doaj.org/article/03bd15395b1940af8a64eb293314b127
Autor:
Massimo Salvi, Bruno De Santi, Bianca Pop, Martino Bosco, Valentina Giannini, Daniele Regge, Filippo Molinari, Kristen M. Meiburger
Publikováno v:
Journal of Imaging, Vol 8, Iss 5, p 133 (2022)
Magnetic resonance imaging (MRI) has a growing role in the clinical workup of prostate cancer. However, manual three-dimensional (3D) segmentation of the prostate is a laborious and time-consuming task. In this scenario, the use of automated algorith
Externí odkaz:
https://doaj.org/article/142d72b87a244eaaaabf12a8ccba4fd6
Publikováno v:
Applied Sciences, Vol 11, Iss 20, p 9734 (2021)
Optical coherence tomography angiography (OCTA) is a promising technology for the non-invasive imaging of vasculature. Many studies in literature present automated algorithms to quantify OCTA images, but there is a lack of a review on the most common
Externí odkaz:
https://doaj.org/article/6a90fe04fbb14e98ad95033a5b410b88