Technical feasibility of automated blur detection in digital mammography using convolutional neural network
S Nowakowska, V Vescoli, T Schnitzler… - European Radiology …, 2024 - Springer
Background The presence of a blurred area, depending on its localization, in a mammogram
can limit diagnostic accuracy. The goal of this study was to develop a model for automatic …
can limit diagnostic accuracy. The goal of this study was to develop a model for automatic …
Deep learning versus the human visual system for detecting motion blur in radiography
R Tanaka, S Nozaki, F Goshima… - Journal of Medical …, 2022 - spiedigitallibrary.org
Purpose: The necessity of image retakes is initially determined on a preview monitor
equipped with an operating system; therefore, some image blurring is only noticed later, on …
equipped with an operating system; therefore, some image blurring is only noticed later, on …
[PDF][PDF] Deep Learning Approach for Blur Detection of Digital Breast Tomosynthesis Images
Image quality is critical in domains such as computer vision, image processing, and pattern
recognition. One of the areas of image processing where image quality is critical is image …
recognition. One of the areas of image processing where image quality is critical is image …
CNN-SVM with Data Augmentation for Robust Blur Detection of Digital Breast Tomosynthesis Images
Digital breast tomosynthesis (DBT) is a method that extends digital mammography by
capturing pictures of the breast from various angles of the x-ray source. DBT's angular …
capturing pictures of the breast from various angles of the x-ray source. DBT's angular …
Is it blur or is it texture? An analysis of computational blur and texture measures commonly used in medical image analysis
Purpose In this work, we endeavor to investigate how texture information may contribute to
the response of a blur measure (BM) with motivation rooted in mammography. This is vital as …
the response of a blur measure (BM) with motivation rooted in mammography. This is vital as …
Terahertz Time-domain Spectroscopy (THz-TDS) for classification of blueberries according to their maturity
JO Cruz - 2020 IEEE Engineering International Research …, 2020 - ieeexplore.ieee.org
Non-destructive determination of blueberry compound using spectral detection method is
still a challenge due to the spectral THZ variation caused by abundant biological variations …
still a challenge due to the spectral THZ variation caused by abundant biological variations …
Methods and systems for digital mammography imaging
PM de Carvalho, BG Leh, JC Espino… - US Patent …, 2023 - Google Patents
2020-02-25 Assigned to GE Precision Healthcare LLC reassignment GE Precision
Healthcare LLC ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR …
Healthcare LLC ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR …
Performance Analysis of Mammogram Tumor Classification using Deep Belief Network
MS Karthik, NPG Bhavani - 2023 International Conference on …, 2023 - ieeexplore.ieee.org
Aim: The main aim of the research is to analyze theperformance analysis of mammogram
tumor image classification using Deep Belief Network (DBN) over Decision Tree (DT) with …
tumor image classification using Deep Belief Network (DBN) over Decision Tree (DT) with …
深層学習を用いた単純 X 線撮影における患者体動による不鋭の低減
奥村英一郎， 鈴木伸忠， 奥村恵理香， 北村茂三… - 医用画像情報学会 …, 2023 - jstage.jst.go.jp
抄録 In radiographic examination, in case of the patient's body movement or incomplete
breath-holding, radiography was retaken again. Therefore, we investigated in U-net, Cycle …
breath-holding, radiography was retaken again. Therefore, we investigated in U-net, Cycle …