One-Step Deep Learning Approach to Ultrasound Image Formation and Image Segmentation with a Fully Convolutional Neural Network

2019 ◽  
Author(s):  
Arun Asokan Nair ◽  
Trac D. Tran ◽  
Austin Reiter ◽  
Muyinatu A. Lediju Bell
Keyword(s):  
Neural Network ◽  
Image Segmentation ◽  
Deep Learning ◽  
Convolutional Neural Network ◽  
Ultrasound Image ◽  
Image Formation ◽  
Learning Approach ◽  
One Step

Real-time automatic surgical phase recognition in laparoscopic sigmoidectomy using the convolutional neural network-based deep learning approach

2019 ◽  
Vol 34 (11) ◽  
pp. 4924-4931 ◽  
Author(s):  
Daichi Kitaguchi ◽  
Nobuyoshi Takeshita ◽  
Hiroki Matsuzaki ◽  
Hiroaki Takano ◽  
Yohei Owada ◽  
...  
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Convolutional Neural Network ◽  
Real Time ◽  
Learning Approach ◽  
Laparoscopic Sigmoidectomy ◽  
Phase Recognition

scholarly journals Conceptual Understanding of Convolutional Neural Network- A Deep Learning Approach

2018 ◽  
Vol 132 ◽  
pp. 679-688 ◽  
Author(s):  
Sakshi Indolia ◽  
Anil Kumar Goswami ◽  
S.P. Mishra ◽  
Pooja Asopa
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Convolutional Neural Network ◽  
Conceptual Understanding ◽  
Learning Approach

scholarly journals Estimating Cervical Vertebral Maturation with a Lateral Cephalogram Using the Convolutional Neural Network

2021 ◽  
Vol 10 (22) ◽  
pp. 5400
Author(s):  
Eun-Gyeong Kim ◽  
Il-Seok Oh ◽  
Jeong-Eun So ◽  
Junhyeok Kang ◽  
Van Nhat Thang Le ◽  
...  
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Convolutional Neural Network ◽  
Region Of Interest ◽  
Bone Maturation ◽  
Lateral Cephalogram ◽  
Step Model ◽  
Lateral Cephalograms ◽  
One Step ◽  
Cervical Vertebral Maturation

Recently, the estimation of bone maturation using deep learning has been actively conducted. However, many studies have considered hand–wrist radiographs, while a few studies have focused on estimating cervical vertebral maturation (CVM) using lateral cephalograms. This study proposes the use of deep learning models for estimating CVM from lateral cephalograms. As the second, third, and fourth cervical vertebral regions (denoted as C2, C3, and C4, respectively) are considerably smaller than the whole image, we propose a stepwise segmentation-based model that focuses on the C2–C4 regions. We propose three convolutional neural network-based classification models: a one-step model with only CVM classification, a two-step model with region of interest (ROI) detection and CVM classification, and a three-step model with ROI detection, cervical segmentation, and CVM classification. Our dataset contains 600 lateral cephalogram images, comprising six classes with 100 images each. The three-step segmentation-based model produced the best accuracy (62.5%) compared to the models that were not segmentation-based.

scholarly journals Large-Scale Text Classification Using Scope-Based Convolutional Neural Network: A Deep Learning Approach

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 171548-171558 ◽  
Author(s):  
Jiaying Wang ◽  
Yaxin Li ◽  
Jing Shan ◽  
Jinling Bao ◽  
Chuanyu Zong ◽  
...  
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Convolutional Neural Network ◽  
Text Classification ◽  
Large Scale ◽  
Learning Approach
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