Joint Transformer and Multi-scale CNN for DCE-MRI Breast Cancer Segmentation

Image manifold revealing for breast lesion segmentation in DCE-MRI.

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is widely used for breast lesion differentiation. Manual segmentation in DCE-MRI is difficult and open to viewer interpretation. In this paper, an automatic segmentation method based on image manifold revealing was introduced to overcome the problems of the currently used method. First, high dimensional datasets were constructed fro...

A Multi-scale CNN for Affordance Segmentation in RGB Images

Given a single RGB image our goal is to label every pixel with an affordance type. By affordance, we mean an object’s capability to readily support a certain human action, without requiring precursor actions. We focus on segmenting the following five affordance types in indoor scenes: ‘walkable’, ‘sittable’, ‘lyable’, ‘reachable’, and ‘movable’. Our approach uses a deep architecture, consisting...

Automated localization of breast cancer in DCE-MRI

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is increasingly being used for the detection and diagnosis of breast cancer. Compared to mammography, DCE-MRI provides higher sensitivity, however its specificity is variable. Moreover, DCE-MRI data analysis is time consuming and depends on reader expertise. The aim of this work is to propose a novel automated breast cancer localiza...

Novel DCE-MRI Technique: Application to Breast Cancer

Introduction: Increased microvessel density and increased permeability of the vascular bed are important biomarkers of malignancy and are detected in aggressive breast cancer. These parameters can be assessed by dynamic contrast-enhanced MRI (DCE-MRI) that has been used to determine the tumor grade, extent of disease, and treatment response (1, 2). In breast cancer DCE-MRI studies have reported...

Automatic MRI Prostate Segmentation based CNN-ASM