Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Filters

Said Pertuz

Showing results (1-10 of 19) with videos related to

Pageof 2
Sort By:
Medical Hypotheses|December 15, 2019
Field cancerization in the understanding of parenchymal analysis of mammograms for breast cancer risk assessmentDavid A Miranda, Said Pertuz
Computer Methods and Programs in Biomedicine|October 16, 2021
Algorithms and methods for computerized analysis of mammography images in breast cancer risk assessmentAngie Hernández, David A Miranda, Said Pertuz
Medical Physics|March 30, 2023
An in silico study on the detectability of field cancerization through parenchymal analysis of digital mammogramsAngie Hernández, David A Miranda, Said Pertuz
Computer Methods and Programs in Biomedicine|December 5, 2025
The added value of radiomic analysis for predicting spontaneous preterm birth in the first trimesterWilliam Cancino, Carlos Hernan Becerra-Mojica, Said Pertuz
IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society|December 11, 2012
Generation of all-in-focus images by noise-robust selective fusion of limited depth-of-field imagesSaid Pertuz, Domenec Puig, Miguel Angel Garcia, et al.
Medical Physics|November 27, 2021
Image retrieval-based parenchymal analysis for breast cancer risk assessmentAstrid Padilla, Otso Arponen, Irina Rinta-Kiikka, et al.
Medical Physics|February 28, 2025
Breast cancer detection from ultrasound computed tomography imaging using radiomic analysis: in silico trialAndres Vargas, Nicole Hernandez, Ana B Ramirez, et al.
Acta Radiologica (Stockholm, Sweden : 1987)|December 20, 2023
Transfer learning for the generalization of artificial intelligence in breast cancer detection: a case-control studyGerson Africano, Otso Arponen, Irina Rinta-Kiikka, et al.
Radiology|October 23, 2015
Fully Automated Quantitative Estimation of Volumetric Breast Density from Digital Breast Tomosynthesis Images: Preliminary Results and Comparison with Digital Mammography and MR ImagingSaid Pertuz, Elizabeth S McDonald, Susan P Weinstein, et al.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|October 6, 2020
A New Benchmark and Method for the Evaluation of Chest Wall Detection in Digital Mammography<sup>.</sup>Gerson Africano, Otso Arponen, Antti Sassi, et al.
Pageof 2

Showing results (1-10 of 19) with videos related to

Sort By:
Pageof 2
Medical Hypotheses|December 15, 2019
Field cancerization in the understanding of parenchymal analysis of mammograms for breast cancer risk assessmentDavid A Miranda, Said Pertuz
Computer Methods and Programs in Biomedicine|October 16, 2021
Algorithms and methods for computerized analysis of mammography images in breast cancer risk assessmentAngie Hernández, David A Miranda, Said Pertuz
Medical Physics|March 30, 2023
An in silico study on the detectability of field cancerization through parenchymal analysis of digital mammogramsAngie Hernández, David A Miranda, Said Pertuz
Computer Methods and Programs in Biomedicine|December 5, 2025
The added value of radiomic analysis for predicting spontaneous preterm birth in the first trimesterWilliam Cancino, Carlos Hernan Becerra-Mojica, Said Pertuz
IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society|December 11, 2012
Generation of all-in-focus images by noise-robust selective fusion of limited depth-of-field imagesSaid Pertuz, Domenec Puig, Miguel Angel Garcia, et al.
Medical Physics|November 27, 2021
Image retrieval-based parenchymal analysis for breast cancer risk assessmentAstrid Padilla, Otso Arponen, Irina Rinta-Kiikka, et al.
Medical Physics|February 28, 2025
Breast cancer detection from ultrasound computed tomography imaging using radiomic analysis: in silico trialAndres Vargas, Nicole Hernandez, Ana B Ramirez, et al.
Acta Radiologica (Stockholm, Sweden : 1987)|December 20, 2023
Transfer learning for the generalization of artificial intelligence in breast cancer detection: a case-control studyGerson Africano, Otso Arponen, Irina Rinta-Kiikka, et al.
Radiology|October 23, 2015
Fully Automated Quantitative Estimation of Volumetric Breast Density from Digital Breast Tomosynthesis Images: Preliminary Results and Comparison with Digital Mammography and MR ImagingSaid Pertuz, Elizabeth S McDonald, Susan P Weinstein, et al.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|October 6, 2020
A New Benchmark and Method for the Evaluation of Chest Wall Detection in Digital Mammography<sup>.</sup>Gerson Africano, Otso Arponen, Antti Sassi, et al.
Pageof 2