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Low-rank Convex/Sparse Thermal Matrix Approximation for Infrared-based Diagnostic System

14 Oct 2020

Active and passive thermography are two efficient techniques extensively used to measure heterogeneous thermal patterns leading to subsurface defects for diagnostic evaluations.

BREAST CANCER DETECTION DEFECT DETECTION MATRIX FACTORIZATION / DECOMPOSITION

ESTAN: Enhanced Small Tumor-Aware Network for Breast Ultrasound Image Segmentation

27 Sep 2020

Breast tumor segmentation is a critical task in computer-aided diagnosis (CAD) systems for breast cancer detection because accurate tumor size, shape and location are important for further tumor quantification and classification.

BREAST CANCER DETECTION TUMOR SEGMENTATION

Explainable Disease Classification via weakly-supervised segmentation

24 Aug 2020

Results of testing on on a large public dataset show that with just a third of images with roughly segmented fluid filled regions, the classification accuracy is on par with state of the art methods while providing a good explanation in the form of anatomically accurate heatmap /region of interest.

BREAST CANCER DETECTION GENERAL CLASSIFICATION IMAGE CLASSIFICATION WEAKLY SUPERVISED SEGMENTATION

Computer-aided Tumor Diagnosis in Automated Breast Ultrasound using 3D Detection Network

31 Jul 2020

The efficacy of our network is verified from a collected dataset of 418 patients with 145 benign tumors and 273 malignant tumors.

BREAST CANCER DETECTION GENERAL CLASSIFICATION

Artificial Neural Network Based Breast Cancer Screening: A Comprehensive Review

29 May 2020

The advantages and limitations of different ANN models including spiking neural network (SNN), deep belief network (DBN), convolutional neural network (CNN), multilayer neural network (MLNN), stacked autoencoders (SAE), and stacked de-noising autoencoders (SDAE) are described in this review.

BREAST CANCER DETECTION

Breast Cancer Detection Using Convolutional Neural Networks

17 Mar 2020

Breast cancer is prevalent in Ethiopia that accounts 34% among women cancer patients.

ANOMALY DETECTION BREAST CANCER DETECTION REGION PROPOSAL

Learning from Suspected Target: Bootstrapping Performance for Breast Cancer Detection in Mammography

1 Mar 2020

It is worth mention that dense breast typically has a higher risk for developing breast cancers and also are harder for cancer detection in diagnosis, and our method outperforms a reported result from performance of radiologists.

BREAST CANCER DETECTION OBJECT DETECTION

2D Convolutional Neural Networks for 3D Digital Breast Tomosynthesis Classification

27 Feb 2020

Automated methods for breast cancer detection have focused on 2D mammography and have largely ignored 3D digital breast tomosynthesis (DBT), which is frequently used in clinical practice.

BREAST CANCER DETECTION GENERAL CLASSIFICATION