Seismic characterization of deeply buried paleocaves based on Bayesian deep learning

Author(s):  
Guoyin Zhang ◽  
Chengyan Lin ◽  
Lihua Ren ◽  
Shiyin Li ◽  
Shiti Cui ◽  
...  
2021 ◽  
Vol 11 (7) ◽  
pp. 3119
Author(s):  
Cristina L. Saratxaga ◽  
Jorge Bote ◽  
Juan F. Ortega-Morán ◽  
Artzai Picón ◽  
Elena Terradillos ◽  
...  

(1) Background: Clinicians demand new tools for early diagnosis and improved detection of colon lesions that are vital for patient prognosis. Optical coherence tomography (OCT) allows microscopical inspection of tissue and might serve as an optical biopsy method that could lead to in-situ diagnosis and treatment decisions; (2) Methods: A database of murine (rat) healthy, hyperplastic and neoplastic colonic samples with more than 94,000 images was acquired. A methodology that includes a data augmentation processing strategy and a deep learning model for automatic classification (benign vs. malignant) of OCT images is presented and validated over this dataset. Comparative evaluation is performed both over individual B-scan images and C-scan volumes; (3) Results: A model was trained and evaluated with the proposed methodology using six different data splits to present statistically significant results. Considering this, 0.9695 (±0.0141) sensitivity and 0.8094 (±0.1524) specificity were obtained when diagnosis was performed over B-scan images. On the other hand, 0.9821 (±0.0197) sensitivity and 0.7865 (±0.205) specificity were achieved when diagnosis was made considering all the images in the whole C-scan volume; (4) Conclusions: The proposed methodology based on deep learning showed great potential for the automatic characterization of colon polyps and future development of the optical biopsy paradigm.


2017 ◽  
Author(s):  
Valentina Zampetti ◽  
Sonia Perrotta ◽  
Ghassen Chaari ◽  
Thomas Krayenbuehl ◽  
Matthias Braun ◽  
...  

Author(s):  
Bilal Hassan ◽  
Shiyin Qin ◽  
Ramsha Ahmed ◽  
Taimur Hassan ◽  
Abdel Hakeem Taguri ◽  
...  
Keyword(s):  

2021 ◽  
Author(s):  
Yi Luo ◽  
Yichen Wu ◽  
Liqiao Li ◽  
Yuening Guo ◽  
Ege Çetintaş ◽  
...  

2021 ◽  
Author(s):  
N. Tragni ◽  
G. Calamita ◽  
L. Lastilla ◽  
V. Belloni ◽  
R. Ravanelli ◽  
...  

2018 ◽  
Vol 43 (10) ◽  
pp. 2219-2231 ◽  
Author(s):  
Velio Coviello ◽  
Lucia Capra ◽  
Rosario Vázquez ◽  
Victor H. Márquez-Ramírez

2017 ◽  
Vol 60 (4) ◽  
Author(s):  
Ettore Cardarelli ◽  
Michele Cercato ◽  
Luciana Orlando

Geosciences ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. 416
Author(s):  
Enrico Paolucci ◽  
Giuseppe Cavuoto ◽  
Giuseppe Cosentino ◽  
Monia Coltella ◽  
Maurizio Simionato ◽  
...  

A first-order seismic characterization of Northern Apulia (Southern Italy) has been provided by considering geological information and outcomes of a low-cost geophysical survey. In particular, 403 single-station ambient vibration measurements (HVSR techniques) distributed within the main settlements of the area have been considered to extract representative patterns deduced by Principal Component Analysis. The joint interpretation of these pieces of information allows the identification of three main domains (Gargano Promontory, Bradanic Through and Southern Apennines Fold and Thrust Belt), each characterized by specific seismic resonance phenomena. In particular, the Bradanic Through is homogeneously characterized by low frequency (<1 Hz) resonance effects associated with relatively deep (>100 m) seismic impedance, which is contrasting corresponding to the buried Apulian carbonate platform and/or sandy horizons located within the Plio-Pleistocene deposits. In the remaining ones, relatively high frequency (>1 Hz) resonance phenomena are ubiquitous due to the presence of shallower impedance contrasts (<100 m), which do not always correspond to the top of the geological bedrock. These general indications may be useful for a preliminary regional characterization of seismic response in the study area, which can be helpful for an effective planning of more detailed studies targeted to engineering purposes.


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