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Computer aided detection and diagnosis in medical imaging

https://doi.org/10.1145/3012430.3012567
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/cncr.25081openalex-snapshot
Breast cancer risk estimation with artificial neural networks revisited
inferredcites →https://doi.org/10.1007/978-3-319-19992-4_46openalex-snapshot
Multi-scale Convolutional Neural Networks for Lung Nodule Classification
inferredcites →https://doi.org/10.1007/s10278-013-9622-7openalex-snapshot
The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository
inferredcites →https://doi.org/10.1016/j.acra.2005.04.011openalex-snapshot
CAD-Aided Mammogram Training1
inferredcites →https://doi.org/10.1016/j.acra.2005.06.017openalex-snapshot
How Can a Massive Training Artificial Neural Network (MTANN) Be Trained With a Small Number of Cases in the Distinction Between Nodules and Vessels in Thoracic CT?1
inferredcites →https://doi.org/10.1016/j.acra.2009.12.009openalex-snapshot
Neural Network Ensemble-Based Computer-Aided Diagnosis for Differentiation of Lung Nodules on CT Images
inferredcites →https://doi.org/10.1016/j.cmpb.2015.12.014openalex-snapshot
Representation learning for mammography mass lesion classification with convolutional neural networks
inferredcites →https://doi.org/10.1016/j.compmedimag.2007.02.002openalex-snapshot
Computer-aided diagnosis in medical imaging: Historical review, current status and future potential
inferredcites →https://doi.org/10.1016/j.jbi.2015.01.007openalex-snapshot
Modeling false positive error making patterns in radiology trainees for improved mammography education
inferredcites →https://doi.org/10.1017/9781009006767.017openalex-snapshot
Neural Networks and Deep Learning
inferredcites →https://doi.org/10.1038/srep24454openalex-snapshot
Computer-Aided Diagnosis with Deep Learning Architecture: Applications to Breast Lesions in US Images and Pulmonary Nodules in CT Scans
inferredcites →https://doi.org/10.1053/j.semnuclmed.2011.06.004openalex-snapshot
Computer-Aided Diagnosis and Artificial Intelligence in Clinical Imaging
inferredcites →https://doi.org/10.1080/21681163.2015.1131197openalex-snapshot
Computational mammography using deep neural networks
inferredcites →https://doi.org/10.1088/0031-9155/59/4/897openalex-snapshot
Computerized characterization of lung nodule subtlety using thoracic CT images
inferredcites →https://doi.org/10.1109/embc.2015.7318881openalex-snapshot
A unified framework for automatic wound segmentation and analysis with deep convolutional neural networks
inferredcites →https://doi.org/10.1109/tmi.2015.2482920openalex-snapshot
Improving Computer-Aided Detection UsingConvolutional Neural Networks and Random View Aggregation
inferredcites →https://doi.org/10.1109/tmi.2016.2528162openalex-snapshot
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
inferredcites →https://doi.org/10.1109/tmi.2016.2535865openalex-snapshot
Lung Pattern Classification for Interstitial Lung Diseases Using a Deep Convolutional Neural Network
inferredcites →https://doi.org/10.1118/1.2829870openalex-snapshot
Mixture of expert 3D massive-training ANNs for reduction of multiple types of false positives in CAD for detection of polyps in CT colonography
inferredcites →https://doi.org/10.1118/1.3013555openalex-snapshot
Anniversary Paper: History and status of CAD and quantitative image analysis: The role of Medical Physics and AAPM
inferredcites →https://doi.org/10.1118/1.3301575openalex-snapshot
Individualized computer‐aided education in mammography based on user modeling: Concept and preliminary experiments
inferredcites →https://doi.org/10.1118/1.3528204openalex-snapshot
The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI): A Completed Reference Database of Lung Nodules on CT Scans
inferredcites →https://doi.org/10.1118/1.3694096openalex-snapshot
A computerized scheme for lung nodule detection in multiprojection chest radiography
inferredcites →https://doi.org/10.1118/1.4892173openalex-snapshot
Using computer‐extracted image features for modeling of error‐making patterns in detection of mammographic masses among radiology residents
inferredcites →https://doi.org/10.1148/radiographics.20.1.g00ja27257openalex-snapshot
The Radiological Society of North America 85th Scientific Assembly and Annual Meeting
inferredcites →https://doi.org/10.1148/radiol.2453062161openalex-snapshot
CT Colonography with Computer-aided Detection as a Second Reader: Observer Performance Study
inferredcites →https://doi.org/10.1148/rg.347130053openalex-snapshot
CT Colonography with Computer-aided Detection: Recognizing the Causes of False-Positive Reader Results
inferredcites →https://doi.org/10.1155/2012/792079openalex-snapshot
Pixel-Based Machine Learning in Medical Imaging
inferredcites →https://doi.org/10.1155/2015/670739openalex-snapshot
Automatic Segmentation of Colon in 3D CT Images and Removal of Opacified Fluid Using Cascade Feed Forward Neural Network
inferredcites →https://doi.org/10.1186/1472-6947-11-68openalex-snapshot
Towards case-based medical learning in radiological decision making using content-based image retrieval
inferredcites →https://doi.org/10.1186/1475-925x-13-41openalex-snapshot
Computer-aided detection system for lung cancer in computed tomography scans: Review and future prospects
inferredcites →https://doi.org/10.1259/bjr/25777270openalex-snapshot
Computer-aided detection (CAD) for CT colonography: a tool to address a growing need
inferredcites →https://doi.org/10.2147/ott.s80733openalex-snapshot
Computer-aided classification of lung nodules on computed tomography images via deep learning technique
inferredcites →https://doi.org/10.2214/ajr.174.1.1740071openalex-snapshot
Development of a Digital Image Database for Chest Radiographs With and Without a Lung Nodule
inferredcites →https://doi.org/10.2298/csis141230049mopenalex-snapshot
Computer aided mass detection in mammography with temporal change analysis
inferredcites →https://doi.org/10.3233/bme-141102openalex-snapshot
A new method based on MTANNs for cutting down false-positives: An evaluation on different versions of commercial pulmonary nodule detection CAD software
inferredcites →https://doi.org/10.3978/j.issn.2223-4292.2012.09.02openalex-snapshot
A review of computer-aided diagnosis in thoracic and colonic imaging.
inferredcites →https://doi.org/10.5391/ijfis.2012.12.2.137openalex-snapshot
Detection of Lung Nodule on Temporal Subtraction Images Based on Artificial Neural Network

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.4095071openalex-extracted
Testing the Performance, Adequacy, and Applicability of an Artificial Intelligent Model for Pediatric Pneumonia Diagnosis
inferred← citeshttps://doi.org/10.1002/lio2.1008openalex-snapshot
Use of artificial intelligence for the diagnosis of cholesteatoma
inferred← citeshttps://doi.org/10.1007/978-3-030-33128-3_1openalex-snapshot
Deep Learning in Medical Image Analysis
inferred← citeshttps://doi.org/10.1007/978-981-97-5345-1_1openalex-snapshot
Artificial Intelligence in Diagnostic Medical Image Processing for Advanced Healthcare Applications
inferred← citeshttps://doi.org/10.1007/978-981-99-1909-3_5openalex-snapshot
A Comparative Analysis of Different Diagnostic Imaging Modalities
inferred← citeshttps://doi.org/10.1007/s10462-023-10511-6openalex-snapshot
Transition of traditional method to deep learning based computer-aided system for breast cancer using Automated Breast Ultrasound System (ABUS) images: a review
inferred← citeshttps://doi.org/10.1007/s11042-022-13504-9openalex-snapshot
Convolution neural network based model to classify colon cancerous tissue
inferred← citeshttps://doi.org/10.1007/s11042-023-17458-4openalex-snapshot
TE-CapsNet: time efficient capsule network for automatic disease classification from medical images
inferred← citeshttps://doi.org/10.1016/0003-6870(85)90204-2openalex-snapshot
Computer aided technologies
inferred← citeshttps://doi.org/10.1016/j.bspc.2017.11.017openalex-snapshot
An appraisal of nodules detection techniques for lung cancer in CT images
inferred← citeshttps://doi.org/10.1016/j.cmpb.2023.107765openalex-snapshot
Testing the performance, adequacy, and applicability of an artificial intelligence model for pediatric pneumonia diagnosis
inferred← citeshttps://doi.org/10.1016/j.compbiomed.2025.110547openalex-snapshot
Deep neural hashing for content-based medical image retrieval: A survey
inferred← citeshttps://doi.org/10.1016/j.eswa.2018.01.028openalex-snapshot
Optimization of computer aided detection systems: An evolutionary approach
inferred← citeshttps://doi.org/10.1016/j.jacr.2018.03.046openalex-snapshot
Artificial Intelligence and the Practice of Radiology: An Alternative View
inferred← citeshttps://doi.org/10.1016/j.media.2016.06.012openalex-snapshot
Oncological image analysis
inferred← citeshttps://doi.org/10.1017/9781108163781.008openalex-snapshot
Perceptual Factors in Reading Medical Images
inferred← citeshttps://doi.org/10.1088/1361-6560/ab553dopenalex-snapshot
A collection input based support tensor machine for lesion malignancy classification in digital breast tomosynthesis
inferred← citeshttps://doi.org/10.1093/jbi/wbac052openalex-snapshot
Past, Present, and Future of Machine Learning and Artificial Intelligence for Breast Cancer Screening
inferred← citeshttps://doi.org/10.1109/aisc56616.2023.10085348openalex-snapshot
FuzzyNet: Medical Image Classification based on GLCM Texture Feature
inferred← citeshttps://doi.org/10.1109/comm48946.2020.9142032openalex-snapshot
Characterization of Atheroma Plaques Echogenicity and Texture for Computer- Aided Diagnosis in Cardiovascular Diseases
inferred← citeshttps://doi.org/10.1109/ict4m68001.2025.11363489openalex-snapshot
A Comparative Study of Deep Learning Models for Automated Detection of Lumpy Skin Disease (LSD) in Cattle
inferred← citeshttps://doi.org/10.1109/igeht.2017.8094070openalex-snapshot
Feature selection algorithms to improve thyroid disease diagnosis
inferred← citeshttps://doi.org/10.1111/cgf.14333openalex-snapshot
Uncertainty‐aware Visualization in Medical Imaging ‐ A Survey
inferred← citeshttps://doi.org/10.11591/ijece.v9i2.pp992-1001openalex-snapshot
A novel approach to jointly address localization and classification of breast cancer using bio-inspired approach
inferred← citeshttps://doi.org/10.11606/d.18.2019.tde-25042019-110326openalex-snapshot
Detecção de distorção arquitetural mamária em mamografia digital utilizando rede neural convolucional profunda
inferred← citeshttps://doi.org/10.1259/bjr.20190580openalex-snapshot
CAD and AI for breast cancer—recent development and challenges
inferred← citeshttps://doi.org/10.14569/ijacsa.2017.080917openalex-snapshot
Effectiveness of Existing CAD-Based Research Work towards Screening Breast Cancer
inferred← citeshttps://doi.org/10.14569/ijacsa.2023.0140808openalex-snapshot
Detection of Tuberculosis Based on Hybridized Pre-Processing Deep Learning Method
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Down syndrome identification and classification using facial features with neural network
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Electromagnetic Technologies for Medical Diagnostics
inferred← citeshttps://doi.org/10.3390/jcm14051567openalex-snapshot
Computer-Aided Decision Support and 3D Models in Pancreatic Cancer Surgery: A Pilot Study
inferred← citeshttps://doi.org/10.3390/jimaging9030070openalex-snapshot
On The Potential of Image Moments for Medical Diagnosis
inferred← citeshttps://doi.org/10.4018/978-1-5225-2255-3.ch088openalex-snapshot
Sociological Perspectives on Improving Medical Diagnosis Emphasizing CAD
inferred← citeshttps://doi.org/10.4018/978-1-5225-7489-7.ch009openalex-snapshot
Sociological Perspectives on Improving Medical Diagnosis Emphasizing CAD
inferred← citeshttps://doi.org/10.47191/ijcsrr/v6-i8-74openalex-snapshot
Detection and Classification of Gastrointestinal Diseases by using Machine Learning: A Review
inferred← citeshttps://doi.org/10.47749/t/unicamp.2020.1127255openalex-snapshot
Pattern recognition in facial expressions
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Introductory Chapter: Integration of Computer-Aided Technologies in Product Lifecycle Management (PLM) and Human Lifecycle Management (HUM)
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Enhancing Breast Cancer Classification using a Modified GoogLeNet Architecture with Attention Mechanism
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