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Automated Breast Ultrasound Lesions Detection Using Convolutional Neural Networks

IEEE journal of biomedical and health informatics, 2018-07, Vol.22 (4), p.1218-1226

2018

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Deep convolutional neural networks for brain image analysis on magnetic resonance imaging: a review

Artificial intelligence in medicine, 2019-04, Vol.95, p.64-81

2019

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Volumetric breast density estimation from full-field digital mammograms: a validation study

PloS one, 2014-01, Vol.9 (1), p.e85952-e85952

2014

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A survey of prostate segmentation methodologies in ultrasound, magnetic resonance and computed tomography images

Computer methods and programs in biomedicine, 2012-10, Vol.108 (1), p.262-287

2012

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Breast MRI and X-ray mammography registration using gradient values

Medical image analysis, 2019-05, Vol.54, p.76-87

2019

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DermoExpert: Skin lesion classification using a hybrid convolutional neural network through segmentation, transfer learning, and augmentation

Informatics in medicine unlocked, 2022, Vol.28, p.100819, Article 100819

2022

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A Novel Breast Tissue Density Classification Methodology

IEEE journal of biomedical and health informatics, 2008-01, Vol.12 (1), p.55-65

2008

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Digital Mammography: 10th International Workshop, IWDM 2010, Girona, Catalonia, Spain, June 16-18, 2010. Proceedings

2010 edition., 2010

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Multimodal Breast Parenchymal Patterns Correlation Using a Patient-Specific Biomechanical Model

IEEE transactions on medical imaging, 2018-03, Vol.37 (3), p.712-723

2018

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Lesion Segmentation in Automated 3D Breast Ultrasound: Volumetric Analysis

Ultrasonic imaging, 2018-03, Vol.40 (2), p.97-112

2018

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A Method for 6D Pose Estimation of Free-Form Rigid Objects Using Point Pair Features on Range Data

Sensors (Basel, Switzerland), 2018-08, Vol.18 (8), p.2678

2018

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Local breast density assessment using reacquired mammographic images

European journal of radiology, 2017-08, Vol.93, p.121-127

2017

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FoPro-KD: Fourier Prompted Effective Knowledge Distillation for Long-Tailed Medical Image Recognition

IEEE transactions on medical imaging, 2024-03, Vol.43 (3), p.954-965

2024

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Brickognize: Applying Photo-Realistic Image Synthesis for Lego Bricks Recognition with Limited Data

Sensors (Basel, Switzerland), 2023-02, Vol.23 (4), p.1898

2023

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Breast ultrasound region of interest detection and lesion localisation

Artificial intelligence in medicine, 2020-07, Vol.107, p.101880-101880, Article 101880

2020

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Deep learning for mass detection in Full Field Digital Mammograms

Computers in biology and medicine, 2020-06, Vol.121, p.103774-103774, Article 103774

2020

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A Review on Automatic Mammographic Density and Parenchymal Segmentation

International Journal of Breast Cancer, 2015-01, Vol.2015 (2015), p.65-95

2015

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Automatic mass detection in mammograms using deep convolutional neural networks

Journal of medical imaging (Bellingham, Wash.), 2019-07, Vol.6 (3), p.031409-031409

2019

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DSNet: Automatic dermoscopic skin lesion segmentation

Computers in biology and medicine, 2020-05, Vol.120, p.103738-103738, Article 103738

2020

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A U-Net Ensemble for breast lesion segmentation in DCE MRI

Computers in biology and medicine, 2022-01, Vol.140, p.105093-105093, Article 105093

2022

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Automated detection of multiple sclerosis lesions in serial brain MRI

Neuroradiology, 2012-08, Vol.54 (8), p.787-807

2012

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Challenges of deep learning methods for COVID-19 detection using public datasets

Informatics in medicine unlocked, 2022, Vol.30, p.100945-100945, Article 100945

2022

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A supervised learning framework of statistical shape and probability priors for automatic prostate segmentation in ultrasound images

Medical image analysis, 2013-08, Vol.17 (6), p.587-600

2013

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Which is the best way to organize/classify images by content?

Image and vision computing, 2007-06, Vol.25 (6), p.778-791

2007

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Visual Attention and Color Cues for 6D Pose Estimation on Occluded Scenarios Using RGB-D Data

Sensors (Basel, Switzerland), 2021-12, Vol.21 (23), p.8090

2021

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Automated Breast Ultrasound Lesions Detection Using Convolutional Neural Networks

Deep convolutional neural networks for brain image analysis on magnetic resonance imaging: a review

Volumetric breast density estimation from full-field digital mammograms: a validation study

A survey of prostate segmentation methodologies in ultrasound, magnetic resonance and computed tomography images

Breast MRI and X-ray mammography registration using gradient values

DermoExpert: Skin lesion classification using a hybrid convolutional neural network through segmentation, transfer learning, and augmentation

A Novel Breast Tissue Density Classification Methodology

Digital Mammography: 10th International Workshop, IWDM 2010, Girona, Catalonia, Spain, June 16-18, 2010. Proceedings

Multimodal Breast Parenchymal Patterns Correlation Using a Patient-Specific Biomechanical Model

Lesion Segmentation in Automated 3D Breast Ultrasound: Volumetric Analysis

A Method for 6D Pose Estimation of Free-Form Rigid Objects Using Point Pair Features on Range Data

Local breast density assessment using reacquired mammographic images

FoPro-KD: Fourier Prompted Effective Knowledge Distillation for Long-Tailed Medical Image Recognition

Brickognize: Applying Photo-Realistic Image Synthesis for Lego Bricks Recognition with Limited Data

Breast ultrasound region of interest detection and lesion localisation

Deep learning for mass detection in Full Field Digital Mammograms

A Review on Automatic Mammographic Density and Parenchymal Segmentation

Automatic mass detection in mammograms using deep convolutional neural networks

DSNet: Automatic dermoscopic skin lesion segmentation

A U-Net Ensemble for breast lesion segmentation in DCE MRI

Automated detection of multiple sclerosis lesions in serial brain MRI

Challenges of deep learning methods for COVID-19 detection using public datasets

A supervised learning framework of statistical shape and probability priors for automatic prostate segmentation in ultrasound images

Which is the best way to organize/classify images by content?

Visual Attention and Color Cues for 6D Pose Estimation on Occluded Scenarios Using RGB-D Data

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