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Computer Vision and Pattern Recognition 2020

Zeynep Akata, Andreas Geiger, Torsten Sattler • International Journal of Computer Vision (2021)

This special issue covers a wide range of topics from the area of Computer Vision, Pattern Recognition, and Machine Learning.This breadth of scope is reflected by the papers included in this special issue, which touch topics including geome...

OPENALEX cc-by DOI: https://doi.org/10.1007/s11263-021-01522-3

Evaluation of Similarity of Image Explanations Produced by SHAP, LIME and Grad-CAM

Vladyslav Yavtukhovskyi, Violeta Tretynyk • Кібернетика та комп'ютерні технології (2025)

Introduction. Convolutional neural networks (CNNs) are a subtype of neural networks developed specifically to work with images [1]. They have achieved great success both in research and in practical applications in recent years, however, on...

DOAJ Open Access (DOAJ) DOI: 10.34229/2707-451X.25.2.6

Deep learning in medical image registration: a review

Yabo Fu, Yang Lei, Tonghe Wang, Walter John Curran et al. • Physics in Medicine and Biology (2020)

This paper presents a review of deep learning (DL)-based medical image registration methods. We summarized the latest developments and applications of DL-based registration methods in the medical field. These methods were classified into se...

OPENALEX Open Access DOI: https://doi.org/10.1088/1361-6560/ab843e PMC: 7759388

Deep Learning in Microscopy Image Analysis: A Survey

Fuyong Xing, Yuanpu Xie, Hai Su, Fujun Liu et al. • IEEE Transactions on Neural Networks and Learning Systems (2017)

Computerized microscopy image analysis plays an important role in computer aided diagnosis and prognosis. Machine learning techniques have powered many aspects of medical investigation and clinical practice. Recently, deep learning is emerg...

OPENALEX DOI: https://doi.org/10.1109/tnnls.2017.2766168

Review of deep learning for photoacoustic imaging

Changchun Yang, Hengrong Lan, Feng Gao, Fei Gao • Photoacoustics (2020)

Machine learning has been developed dramatically and witnessed a lot of applications in various fields over the past few years. This boom originated in 2009, when a new model emerged, that is, the deep artificial neural network, which began...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1016/j.pacs.2020.100215 PMC: 7779783

Deep learning for cardiovascular medicine: a practical primer

Chayakrit Krittanawong, Kipp W. Johnson, Robert S. Rosenson, Zhen Wang et al. • European Heart Journal (2019)

Deep learning (DL) is a branch of machine learning (ML) showing increasing promise in medicine, to assist in data classification, novel disease phenotyping and complex decision making. Deep learning is a form of ML typically implemented via...

OPENALEX Open Access DOI: https://doi.org/10.1093/eurheartj/ehz056 PMC: 6600129

Medical image segmentation using deep learning: A survey

Risheng Wang, Tao Lei, Ruixia Cui, Bingtao Zhang et al. • IET Image Processing (2022)

Abstract Deep learning has been widely used for medical image segmentation and a large number of papers has been presented recording the success of deep learning in the field. A comprehensive thematic survey on medical image segmentation us...

OPENALEX cc-by DOI: https://doi.org/10.1049/ipr2.12419

An overview of deep learning in medical imaging focusing on MRI

Alexander Selvikvåg Lundervold, Arvid Lundervold • Zeitschrift für Medizinische Physik (2018)

What has happened in machine learning lately, and what does it mean for the future of medical image analysis? Machine learning has witnessed a tremendous amount of attention over the last few years. The current boom started around 2009 when...

OPENALEX cc-by DOI: https://doi.org/10.1016/j.zemedi.2018.11.002

Deep learning approaches to biomedical image segmentation

Intisar Rizwan I Haque, Jeremiah J. Neubert • Informatics in Medicine Unlocked (2020)

The review covers automatic segmentation of images by means of deep learning approaches in the area of medical imaging. Current developments in machine learning, particularly related to deep learning, are proving instrumental in identificat...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1016/j.imu.2020.100297

Image Segmentation Using Deep Learning: A Survey

Shervin Minaee, Yuri Y. Boykov, Fatih Porikli, Antonio Plaza et al. • IEEE Transactions on Pattern Analysis and Machine Intelligence (2021)

Image segmentation is a key task in computer vision and image processing with important applications such as scene understanding, medical image analysis, robotic perception, video surveillance, augmented reality, and image compression, amon...

OPENALEX Open Access DOI: https://doi.org/10.1109/tpami.2021.3059968

A review on deep learning in medical image analysis

S. Suganyadevi, V. Seethalakshmi, K. Balasamy • International Journal of Multimedia Information Retrieval (2021)

Ongoing improvements in AI, particularly concerning deep learning techniques, are assisting to identify, classify, and quantify patterns in clinical images. Deep learning is the quickest developing field in artificial intelligence and is ef...

OPENALEX other-oa DOI: https://doi.org/10.1007/s13735-021-00218-1 PMC: 8417661

Deep Learning and Its Applications in Biomedicine

Chensi Cao, Feng Liu, Hai Tan, Deshou Song et al. • Genomics Proteomics & Bioinformatics (2018)

Advances in biological and medical technologies have been providing us explosive volumes of biological and physiological data, such as medical images, electroencephalography, genomic and protein sequences. Learning from these data facilitat...

OPENALEX cc-by DOI: https://doi.org/10.1016/j.gpb.2017.07.003 PMC: 6000200