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Breast Cancer Detection

8 papers with code ยท Medical
Subtask of Cancer

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Validation of a deep learning mammography model in a population with low screening rates

1 Nov 2019

We specifically explore how a deep learning algorithm trained on screening mammograms from the US and UK generalizes to mammograms collected at a hospital in China, where screening is not widely implemented.

BREAST CANCER DETECTION

Distill-to-Label: Weakly Supervised Instance Labeling Using Knowledge Distillation

26 Jul 2019

Weakly supervised instance labeling using only image-level labels, in lieu of expensive fine-grained pixel annotations, is crucial in several applications including medical image analysis.

BREAST CANCER DETECTION INSTANCE SEGMENTATION MULTIPLE INSTANCE LEARNING SEMANTIC SEGMENTATION

Improving Breast Cancer Detection using Symmetry Information with Deep Learning

17 Aug 2018

At candidate level, AUC value of 0. 933 with 95% confidence interval of [0. 920, 0. 954] was obtained when symmetry information is incorporated in comparison with baseline architecture which yielded AUC value of 0. 929 with [0. 919, 0. 947] confidence interval.

BREAST CANCER DETECTION

Conditional Infilling GANs for Data Augmentation in Mammogram Classification

21 Jul 2018

Deep learning approaches to breast cancer detection in mammograms have recently shown promising results.

BREAST CANCER DETECTION DATA AUGMENTATION

Circular Antenna Array Design for Breast Cancer Detection

15 Jan 2018

Microwave imaging for breast cancer detection is based on the contrast in the electrical properties of healthy fatty breast tissues.

BREAST CANCER DETECTION

Deep Learning Diffuse Optical Tomography

4 Dec 2017

Diffuse optical tomography (DOT) has been investigated as an alternative imaging modality for breast cancer detection thanks to its excellent contrast to hemoglobin oxidization level.

BREAST CANCER DETECTION

A Novel Low-Complexity Framework in Ultra-Wideband Imaging for Breast Cancer Detection

8 Sep 2017

In this research work, a novel framework is pro- posed as an efficient successor to traditional imaging methods for breast cancer detection in order to decrease the computational complexity.

BREAST CANCER DETECTION