Cargando…

Deep Learning in Medical Imaging

Mostrar otras versiones (1)

The artificial neural network (ANN), one of the machine learning (ML) algorithms, inspired by the human brain system, was developed by connecting layers with artificial neurons. However, due to the low computing power and insufficient learnable data, ANN has suffered from overfitting and vanishing g...

Descripción completa

Detalles Bibliográficos
Autores principales:	Kim, Mingyu, Yun, Jihye, Cho, Yongwon, Shin, Keewon, Jang, Ryoungwoo, Bae, Hyun-jin, Kim, Namkug
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Korean Spinal Neurosurgery Society 2019
Materias:	Review Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6945006/ https://www.ncbi.nlm.nih.gov/pubmed/31905454 http://dx.doi.org/10.14245/ns.1938396.198

Ejemplares similares

Deep Learning in Medical Imaging
por: Kim, Mingyu, et al.
Publicado: (2020)

Deep-learning-based image quality enhancement of compressed sensing magnetic resonance imaging of vessel wall: comparison of self-supervised and unsupervised approaches
por: Eun, Da-in, et al.
Publicado: (2020)

Prediction of osteoporosis from simple hip radiography using deep learning algorithm
por: Jang, Ryoungwoo, et al.
Publicado: (2021)

Deep Learning in Medical Imaging: General Overview
por: Lee, June-Goo, et al.
Publicado: (2017)

Can deep learning reduce the time and effort required for manual segmentation in 3D reconstruction of MRI in rotator cuff tears?
por: Kim, Hyojune, et al.
Publicado: (2022)

An Open Medical Platform to Share Source Code and Various Pre-Trained Weights for Models to Use in Deep Learning Research
por: Kim, Sungchul, et al.
Publicado: (2021)

Diagnosis of osteoporotic vertebral compression fractures and fracture level detection using multitask learning with U-Net in lumbar spine lateral radiographs
por: Ryu, Seung Min, et al.
Publicado: (2023)

Emergency triage of brain computed tomography via anomaly detection with a deep generative model
por: Lee, Seungjun, et al.
Publicado: (2022)

Development and validation of a hybrid deep learning–machine learning approach for severity assessment of COVID-19 and other pneumonias
por: Park, Doohyun, et al.
Publicado: (2023)

A Perlin Noise-Based Augmentation Strategy for Deep Learning with Small Data Samples of HRCT Images
por: Bae, Hyun-Jin, et al.
Publicado: (2018)

Efficient Segmentation for Left Atrium With Convolution Neural Network Based on Active Learning in Late Gadolinium Enhancement Magnetic Resonance Imaging
por: Cho, Yongwon, et al.
Publicado: (2022)

Assessment of the Robustness of Convolutional Neural Networks in Labeling Noise by Using Chest X-Ray Images From Multiple Centers
por: Jang, Ryoungwoo, et al.
Publicado: (2020)

Deep learning-based classification with improved time resolution for physical activities of children
por: Jang, Yongwon, et al.
Publicado: (2018)

Deep into the Brain: Artificial Intelligence in Stroke Imaging
por: Lee, Eun-Jae, et al.
Publicado: (2017)

Intravesical Bladder Treatment and Deep Learning Applications to Improve Irritative Voiding Symptoms Caused by Interstitial Cystitis: A Literature Review
por: Cho, Yongwon, et al.
Publicado: (2023)

An Image Turing Test on Realistic Gastroscopy Images Generated by Using the Progressive Growing of Generative Adversarial Networks
por: Shin, Keewon, et al.
Publicado: (2023)

Convolutional Neural Network Technology in Endoscopic Imaging: Artificial Intelligence for Endoscopy
por: Choi, Joonmyeong, et al.
Publicado: (2020)

Realistic high-resolution lateral cephalometric radiography generated by progressive growing generative adversarial network and quality evaluations
por: Kim, Mingyu, et al.
Publicado: (2021)

Overcoming the Challenges in the Development and Implementation of Artificial Intelligence in Radiology: A Comprehensive Review of Solutions Beyond Supervised Learning
por: Hong, Gil-Sun, et al.
Publicado: (2023)

Reproducibility of abnormality detection on chest radiographs using convolutional neural network in paired radiographs obtained within a short-term interval
por: Cho, Yongwon, et al.
Publicado: (2020)

Author Correction: Realistic high-resolution lateral cephalometric radiography generated by progressive growing generative adversarial network and quality evaluations
por: Kim, Mingyu, et al.
Publicado: (2021)

Realistic High-Resolution Body Computed Tomography Image Synthesis by Using Progressive Growing Generative Adversarial Network: Visual Turing Test
por: Park, Ho Young, et al.
Publicado: (2021)

Deep-Learning-Based Automated Rotator Cuff Tear Screening in Three Planes of Shoulder MRI
por: Lee, Kyu-Chong, et al.
Publicado: (2023)

Deep semi-supervised learning for automatic segmentation of inferior alveolar nerve using a convolutional neural network
por: Lim, Ho-Kyung, et al.
Publicado: (2021)

Oropharyngeal squamous cell carcinoma: radiomic machine-learning classifiers from multiparametric MR images for determination of HPV infection status
por: Suh, Chong Hyun, et al.
Publicado: (2020)

Applying Deep Learning in Medical Images: The Case of Bone Age Estimation
por: Lee, Jang Hyung, et al.
Publicado: (2018)

Deep Learning for Medical Image Analysis
por: Senaras, Caglar, et al.
Publicado: (2018)

A Curriculum Learning Strategy to Enhance the Accuracy of Classification of Various Lesions in Chest-PA X-ray Screening for Pulmonary Abnormalities
por: Park, Beomhee, et al.
Publicado: (2019)

Effective End-to-End Deep Learning Process in Medical Imaging Using Independent Task Learning: Application for Diagnosis of Maxillary Sinusitis
por: Oh, Jang-Hoon, et al.
Publicado: (2021)

Development of Deep-Learning-Based Single-Molecule Localization Image Analysis
por: Hyun, Yoonsuk, et al.
Publicado: (2022)

Explainable Deep Learning Models in Medical Image Analysis
por: Singh, Amitojdeep, et al.
Publicado: (2020)

Deep Learning in Medical Hyperspectral Images: A Review
por: Cui, Rong, et al.
Publicado: (2022)

Deep Learning for Medical Image-Based Cancer Diagnosis
por: Jiang, Xiaoyan, et al.
Publicado: (2023)

Synthesizing realistic high-resolution retina image by style-based generative adversarial network and its utilization
por: Kim, Mingyu, et al.
Publicado: (2022)

Deep Learning Approaches for Automatic Localization in Medical Images
por: Alaskar, H., et al.
Publicado: (2022)

A Fully Automated System Using A Convolutional Neural Network to Predict Renal Allograft Rejection: Extra-validation with Giga-pixel Immunostained Slides
por: Kim, Young-Gon, et al.
Publicado: (2019)

Deep Learning-Based Image Reconstruction for Different Medical Imaging Modalities
por: Yaqub, Muhammad, et al.
Publicado: (2022)

Deep Learning in the Medical Domain: Predicting Cardiac Arrest Using Deep Learning
por: Lee, Youngnam, et al.
Publicado: (2018)

Prediction of Mortality after Burn Surgery in Critically Ill Burn Patients Using Machine Learning Models
por: Park, Ji Hyun, et al.
Publicado: (2022)

Intraoperative Neurophysiology Monitoring for Spinal Dysraphism
por: Kim, Keewon
Publicado: (2021)

Cannot write session to /tmp/vufind_sessions/sess_s54svcb6mibbom0t4d9tilkbs5