conclusion the possibility of malignancy is strongly indicated when additional nme lesions show linear or segmental enhancement on preoperative 3t dce-mri in patients with recently diagnosed breast cancer. results on histopathologic analysis of the 88 nme lesions, 73 (83%) were malignant and 15 (17%) were benign. lesion size did not differ significantly between malignant and benign lesions (p =...

<p>Breast ultrasound images are highly valuable for the early detection of breast cancer. However, drawback these is low-quality resolution and presence speckle noise, which affects their interpretability makes them radiologists’ expertise-dependent. As medical images, datasets scarce imbalanced, annotating tedious time-consuming. Transfer learning, as a deep learning technique, can be us...

1. Purpose Dynamic contrast enhanced breast MRI (DCE BMRI) has emerged as tool for breast cancer diagnosis. While DCE BMRI is known to have a high sensitivity studies show a limited specificity of the method, leading to a large number of benign lesions being biopsied. The present paper is part of an effort to address the clinical demand for computer-aided diagnosis tools to support radiologists...

objectives the aim of this study was to evaluate the value of diffusion weighted imaging in diffusion weighted imaging in distinguishing between in benign and malignant breast lesion methods there were 37 female patients with 47 lesions. sixty seven female subjectd (40 mean age ) ,age ranges 17-69 , with histopathologically proven breast lesions underwent dwi of breasts with a single shot echo ...

Purpose: Non-cancerous prostate lesions such as prostate calcification, prostate enlargement, and prostate inflammation cause too many problems for men’s health. This research proposes a novel approach, a combination of image processing techniques and deep learning methods for classification and segmentation of the prostate in CT-scan images by considering the experienced physicians’ reports. ...

Breast lesion segmentation in magnetic resonance (MR) images is one of the most important parts of clinical diagnostic tools. Pixel classification methods have been frequently used in image segmentation with two supervised and unsupervised approaches up to now. Supervised segmentation methods lead to high accuracy, but they need a large amount of labeled data, which is hard, expensive, and slow...

This paper proposes a new approach for computer-aided diagnosis (CAD) system with automatic contouring and texture analysis to aid in the classification of breast lesions using ultrasound. First, the goal is to remove the speckle noise while preserving important information from the lesion boundaries, anisotropic diffusion filtering is applied to the ultrasonic image. A morphological watershed ...

background and objectives:breast cancer is the most common cancer among women worldwide. fine needle aspiration biopsy (fnab) is one of the methods of breast biopsy which is fast, easy and cost effective. the aim of this study was to evaluate the concordance rate between pathologic results of sonography or stereotaxy guided fnab and guided core needle biopsy (cnb) in the evaluation of breast le...

Abstract Automatic segmentation of breast cancer lesions in dynamic contrast-enhanced magnetic resonance imaging is challenged by low accuracy delineation the infiltration area, variable structure and shapes, large intensity heterogeneity changes, boundary contrast. This study constructed a two-stage image framework proposes novel lesion model (TR-IMUnet). The benchmark U-Net network enables ro...