21.1.1 Medical Applications, Diagonistic Systems, General Diagnosis, Therapy Systems

Chapter Contents (Back)
Medical, Applications. Application, Medical. Diagnosis.

Jannin, P., Fitzpatrick, J.M., Hawkes, D.J., Pennec, X., Shahidl, R., Vannier, M.W.,
Validation of medical image processing in image-guided therapy,
MedImg(21), No. 12, December 2002, pp. 1445-1449.
IEEE Top Reference. 0301
BibRef

Lashkia, G.V.[George V.], Anthony, L.[Laurence],
An inductive learning method for medical diagnosis,
PRL(24), No. 1-3, January 2003, pp. 273-282.
Elsevier DOI 0211
BibRef

Stayton, P.S., Hoffman, A.S., El-Sayed, M., Kulkarni, S., Shimoboji, T., Murthy, N., Bulmus, V., Lackey, C.,
Intelligent Biohybrid Materials for Therapeutic and Imaging Agent Delivery,
PIEEE(93), No. 4, April 2005, pp. 726-736.
IEEE DOI 0504
BibRef

Ribeiro, M.X., Traina, A.J.M., Traina, C., Azevedo-Marques, P.M.,
An Association Rule-Based Method to Support Medical Image Diagnosis With Efficiency,
MultMed(10), No. 2, February 2008, pp. 277-285.
IEEE DOI 0905
BibRef

Parekh, R.[Ranjan],
Using Texture Analysis for Medical Diagnosis,
MultMedMag(19), No. 1, January-March 2012, pp. 28-37.
IEEE DOI 1202
BibRef

Lazzarini, N.[Nicola], Nanni, L.[Loris], Fantozzi, C.[Carlo], Pietracaprina, A.[Andrea], Pucci, G.[Geppino], Seccia, T.M.[Teresa Maria], Rossi, G.P.[Gian Paolo],
Heterogeneous machine learning system for improving the diagnosis of primary aldosteronism,
PRL(65), No. 1, 2015, pp. 124-130.
Elsevier DOI 1511
Primary aldosteronism BibRef

Batmanghelich, N.K., Dalca, A.V., Quon, G., Sabuncu, M.R., Golland, P.,
Probabilistic Modeling of Imaging, Genetics and Diagnosis,
MedImg(35), No. 7, July 2016, pp. 1765-1779.
IEEE DOI 1608
Bayes methods BibRef

Sethi, G.[Gaurav], Saini, B.S.,
Computer Aided Diagnosis of Abdomen Diseases Using Curvelet Transform,
IJIG(16), No. 03, 2016, pp. 1650013.
DOI Link 1608
BibRef

Li, R.[Rui], Shi, P.C.[Peng-Cheng], Pelz, J.[Jeff], Alm, C.O.[Cecilia O.], Haake, A.R.[Anne R.],
Modeling eye movement patterns to characterize perceptual skill in image-based diagnostic reasoning processes,
CVIU(151), No. 1, 2016, pp. 138-152.
Elsevier DOI 1610
BibRef
Earlier: A1, A2, A5, Only:
Image Understanding from Experts' Eyes by Modeling Perceptual Skill of Diagnostic Reasoning Processes,
CVPR13(2187-2194)
IEEE DOI 1309
Visual attention BibRef

Edwards, J.,
Signal Processing at the Heart of a Health-Care Renaissance: As people live longer, new technologies promise better and less costly diagnostic services,
SPMag(33), No. 6, November 2016, pp. 8-11.
IEEE DOI 1609
[Special Reports] Biomedical signal processing; Globalization; Medical services BibRef

Edwards, J.,
Innovative Sensors Promise Longer and Healthier Lives: Signal processing leads to devices that provide faster and more insightful monitoring and diagnoses,
SPMag(34), No. 4, July 2017, pp. 14-17.
IEEE DOI 1708
Biomedical monitoring, Diseases, Magnetic sensors, Medical devices, Sensors, Temperature sensors, Tracking BibRef

Liu, S., Sun, X., Xu, W., Zhang, Y., Dai, J.,
Null Distribution of Volume Under Ordered Three-Class ROC Surface (VUS) With Continuous Measurements,
SPLetters(25), No. 12, December 2018, pp. 1855-1859.
IEEE DOI 1812
health care, Monte Carlo methods, nonparametric statistics, normal distribution, patient diagnosis, recursive estimation, volume under the ROC surface (VUS) BibRef

Gu, D., Li, Y., Jiang, F., Wen, Z., Liu, S., Shi, W., Lu, G., Zhou, C.,
VINet: A Visually Interpretable Image Diagnosis Network,
MultMed(22), No. 7, July 2020, pp. 1720-1729.
IEEE DOI 2007
Visualization, Medical services, Biomedical imaging, Estimation, Computational modeling, Solid modeling, Task analysis, medical diagnostic imaging BibRef

Zhang, Y., Wei, Y., Wu, Q., Zhao, P., Niu, S., Huang, J., Tan, M.,
Collaborative Unsupervised Domain Adaptation for Medical Image Diagnosis,
IP(29), 2020, pp. 7834-7844.
IEEE DOI 2007
Medical diagnostic imaging, Noise measurement, Collaboration, Feature extraction, Task analysis, Training, medical image diagnosis BibRef

Liu, Q.D.[Quan-De], Yu, L.Q.[Le-Quan], Luo, L.Y.[Lu-Yang], Dou, Q.[Qi], Heng, P.A.[Pheng Ann],
Semi-Supervised Medical Image Classification With Relation-Driven Self-Ensembling Model,
MedImg(39), No. 11, November 2020, pp. 3429-3440.
IEEE DOI 2011
Medical diagnostic imaging, Lesions, Feature extraction, Predictive models, Semantics, Semisupervised learning, self-ensembling model BibRef

Ayesha, H.[Hareem], Iqbal, S.[Sajid], Tariq, M.[Mehreen], Abrar, M.[Muhammad], Sanaullah, M.[Muhammad], Abbas, I.[Ishaq], Rehman, A.[Amjad], Niazi, M.F.K.[Muhammad Farooq Khan], Hussain, S.[Shafiq],
Automatic medical image interpretation: State of the art and future directions,
PR(114), 2021, pp. 107856.
Elsevier DOI 2103
Attention mechanism, Automatic captioning, Convolutional neural network (cnn), Deep learning, Medical image caption BibRef

Chen, Z.[Zhen], Guo, X.Q.[Xiao-Qing], Woo, P.Y.M.[Peter Y. M.], Yuan, Y.X.[Yi-Xuan],
Super-Resolution Enhanced Medical Image Diagnosis With Sample Affinity Interaction,
MedImg(40), No. 5, May 2021, pp. 1377-1389.
IEEE DOI 2105
Medical diagnostic imaging, Task analysis, Superresolution, Image resolution, Semantics, Logic gates, Feature extraction, semantic consistency BibRef

Hu, W.X.[Wen-Xing], Meng, X.H.[Xiang-He], Bai, Y.T.[Yun-Tong], Zhang, A.[Aiying], Qu, G.[Gang], Cai, B.[Biao], Zhang, G.[Gemeng], Wilson, T.W.[Tony W.], Stephen, J.M.[Julia M.], Calhoun, V.D.[Vince D.], Wang, Y.P.[Yu-Ping],
Interpretable Multimodal Fusion Networks Reveal Mechanisms of Brain Cognition,
MedImg(40), No. 5, May 2021, pp. 1474-1483.
IEEE DOI 2105
Biological system modeling, Correlation, Feature extraction, Computational modeling, Brain modeling, Diseases, Data models, CAM BibRef

Lu, Y.[Ya], Stathopoulou, T.[Thomai], Vasiloglou, M.F.[Maria F.], Christodoulidis, S.[Stergios], Stanga, Z.[Zeno], Mougiakakou, S.[Stavroula],
An Artificial Intelligence-Based System to Assess Nutrient Intake for Hospitalised Patients,
MultMed(23), 2021, pp. 1136-1147.
IEEE DOI 2105
Databases, Estimation, Image segmentation, Artificial intelligence, Hospitals, Training data, Visualization, Artificial Intelligence, few-shot learning BibRef

Zhou, S.K.[S. Kevin], Greenspan, H.[Hayit], Davatzikos, C.[Christos], Duncan, J.S.[James S.], van Ginneken, B.[Bram], Madabhushi, A.[Anant], Prince, J.L.[Jerry L.], Rueckert, D.[Daniel], Summers, R.M.[Ronald M.],
A Review of Deep Learning in Medical Imaging: Imaging Traits, Technology Trends, Case Studies With Progress Highlights, and Future Promises,
PIEEE(109), No. 5, May 2021, pp. 820-838.
IEEE DOI 2105
Imaging, Medical diagnostic imaging, Image segmentation, Diseases, Task analysis, Medical services, Computed tomography, survey BibRef

Zheng, Y.[Yan], Zheng, Y.[Yuchen], Suehiro, D.[Daiki], Uchida, S.[Seiichi],
Top-rank convolutional neural network and its application to medical image-based diagnosis,
PR(120), 2021, pp. 108138.
Elsevier DOI 2109
Top-rank learning, Representation learning, Medical diagnosis BibRef

Briguglio, W.[William], Moghaddam, P.[Parisa], Yousef, W.A.[Waleed A.], Traoré, I.[Issa], Mamun, M.[Mohammad],
Machine learning in precision medicine to preserve privacy via encryption,
PRL(151), 2021, pp. 148-154.
Elsevier DOI 2110
Machine learning, Encryption, Homomorphic encryption, Precision medicine, Privacy BibRef

Zeng, X.H.[Xian-Hua], Huang, Z.Y.[Zheng-Yi], Xu, L.M.[Li-Ming], Xie, Y.[Yicai],
CP-GAN: Meet the high requirements of diagnose report to medical image by content preservation,
IET-IPR(16), No. 1, 2022, pp. 29-38.
DOI Link 2112
BibRef

Bian, C.[Cheng], Yuan, C.L.[Cheng-Lang], Ma, K.[Kai], Yu, S.[Shuang], Wei, D.[Dong], Zheng, Y.F.[Ye-Feng],
Domain Adaptation Meets Zero-Shot Learning: An Annotation-Efficient Approach to Multi-Modality Medical Image Segmentation,
MedImg(41), No. 5, May 2022, pp. 1043-1056.
IEEE DOI 2205
Biomedical imaging, Image segmentation, Prototypes, Annotations, Data models, Semantics, Training, Zero-shot learning, multi-modality medical image BibRef

Ji, W.[Wei], Yu, S.[Shuang], Wu, J.[Junde], Ma, K.[Kai], Bian, C.[Cheng], Bi, Q.[Qi], Li, J.J.[Jing-Jing], Liu, H.R.[Han-Ruo], Cheng, L.[Li], Zheng, Y.F.[Ye-Feng],
Learning Calibrated Medical Image Segmentation via Multi-rater Agreement Modeling,
CVPR21(12336-12346)
IEEE DOI 2111
Image segmentation, Image analysis, Annotations, Semantics, Predictive models, Pattern recognition BibRef

Chen, X.[Xiaocong], Li, Y.[Yun], Yao, L.[Lina], Adeli, E.[Ehsan], Zhang, Y.[Yu], Wang, X.Z.[Xian-Zhi],
Generative adversarial U-Net for domain-free few-shot medical diagnosis,
PRL(157), 2022, pp. 112-118.
Elsevier DOI 2205
Generative Adversarial Network, U-Net, Data Augmentation, Few-shot Medical Diagnosis BibRef

Cheng, N.[Na], Wang, H.[Huadong], Tang, X.[Xi], Zhang, T.[Tao], Gui, J.[Jie], Zheng, C.H.[Chun-Hou], Xia, J.F.[Jun-Feng],
An Ensemble Framework for Improving the Prediction of Deleterious Synonymous Mutation,
CirSysVideo(32), No. 5, May 2022, pp. 2603-2611.
IEEE DOI 2205
Training, Predictive models, Splicing, Bioinformatics, Logistics, Encoding, Diseases, Deleterious synonymous mutation, pathogenicity prediction BibRef

Dai, W.H.[Wei-Hang], Li, X.M.[Xiao-Meng], Chiu, W.H.K.[Wan Hang Keith], Kuo, M.D.[Michael D.], Cheng, K.T.[Kwang-Ting],
Adaptive Contrast for Image Regression in Computer-Aided Disease Assessment,
MedImg(41), No. 5, May 2022, pp. 1255-1268.
IEEE DOI 2205
Task analysis, Estimation, Videos, Image segmentation, X-ray imaging, Bone density, Representation learning, image regression BibRef

Pan, Y.S.[Yong-Sheng], Liu, M.X.[Ming-Xia], Xia, Y.[Yong], Shen, D.G.[Ding-Gang],
Disease-Image-Specific Learning for Diagnosis-Oriented Neuroimage Synthesis With Incomplete Multi-Modality Data,
PAMI(44), No. 10, October 2022, pp. 6839-6853.
IEEE DOI 2209
Diseases, Magnetic resonance imaging, Medical diagnosis, Image synthesis, Generative adversarial networks, Task analysis, brain disease diagnosis BibRef

Zheng, S.[Shuai], Zhu, Z.F.[Zhen-Feng], Liu, Z.Z.[Zhi-Zhe], Guo, Z.Y.[Zhen-Yu], Liu, Y.[Yang], Yang, Y.C.[Yu-Chen], Zhao, Y.[Yao],
Multi-Modal Graph Learning for Disease Prediction,
MedImg(41), No. 9, September 2022, pp. 2207-2216.
IEEE DOI 2209
Diseases, Representation learning, Task analysis, Reliability, Medical diagnostic imaging, Correlation, Adaptation models, latent representation learning BibRef

Zhao, G.M.[Gang-Ming], Feng, Q.L.[Quan-Long], Chen, C.Q.[Chao-Qi], Zhou, Z.[Zhen], Yu, Y.Z.[Yi-Zhou],
Diagnose Like a Radiologist: Hybrid Neuro-Probabilistic Reasoning for Attribute-Based Medical Image Diagnosis,
PAMI(44), No. 11, November 2022, pp. 7400-7416.
IEEE DOI 2210
Medical diagnostic imaging, Cognition, Bayes methods, Diseases, Visualization, Task analysis, Probabilistic logic, neuro-probabilistic reasoning BibRef

Terlapu, P.V.[Panduranga Vital], Gedela, S.B.[Stalin Babu], Gangu, V.K.[Vijay Kumar], Pemula, R.[Rambabu],
Intelligent diagnosis system of hepatitis C virus: A probabilistic neural network based approach,
IJIST(32), No. 6, 2022, pp. 2107-2136.
DOI Link 2212
healthcare, hepatitis C virus, machine learning, probabilistic neural network BibRef

Han, X.M.[Xiang-Min], Wang, J.[Jun], Ying, S.H.[Shi-Hui], Shi, J.[Jun], Shen, D.G.[Ding-Gang],
ML-DSVM+: A meta-learning based deep SVM+ for computer-aided diagnosis,
PR(134), 2023, pp. 109076.
Elsevier DOI 2212
Deep neural network, Support vector machine plus, Learning using privileged information, Meta-learning BibRef

Ravikumar, S., Kannan, E.,
Machine Learning Techniques for Identifying Fetal Risk During Pregnancy,
IJIG(22), No. 5 2022, pp. 2250045.
DOI Link 2212
BibRef

Ge, X.L.[Xiao-Long], Qu, Y.P.[Yan-Ping], Shang, C.J.[Chang-Jing], Yang, L.Z.[Long-Zhi], Shen, Q.[Qiang],
A Self-Adaptive Discriminative Autoencoder for Medical Applications,
CirSysVideo(32), No. 12, December 2022, pp. 8875-8886.
IEEE DOI 2212
Measurement, Feature extraction, Medical diagnostic imaging, Data mining, Face recognition, Deep learning, Autoencoder network, computer aided diagnosis BibRef

Pang, J.[Jianye], Jiang, C.[Cheng], Chen, Y.H.[Yi-Hao], Chang, J.B.[Jian-Bo], Feng, M.[Ming], Wang, R.Z.[Ren-Zhi], Yao, J.H.[Jian-Hua],
3D Shuffle-Mixer: An Efficient Context-Aware Vision Learner of Transformer-MLP Paradigm for Dense Prediction in Medical Volume,
MedImg(42), No. 5, May 2023, pp. 1241-1253.
IEEE DOI 2305
Transformers, Task analysis, Solid modeling, Medical diagnostic imaging, Adaptation models, Image analysis, adaptive scaled shortcut BibRef

Aydogan, M.[Murat],
A hybrid deep neural network-based automated diagnosis system using x-ray images and clinical findings,
IJIST(33), No. 4, 2023, pp. 1368-1382.
DOI Link 2307
clinical findings, deep learning, image processing, text processing, x-ray images BibRef

Wu, X.[Xing], Pei, J.[Jie], Chen, C.[Cheng], Zhu, Y.M.[Yi-Min], Wang, J.[Jianjia], Qian, Q.[Quan], Zhang, J.[Jian], Sun, Q.[Qun], Guo, Y.[Yike],
Federated Active Learning for Multicenter Collaborative Disease Diagnosis,
MedImg(42), No. 7, July 2023, pp. 2068-2080.
IEEE DOI 2307
Federated learning, Collaboration, Medical diagnostic imaging, Training, Deep learning, Hospitals, Labeling, Federated learning, training-efficient BibRef

Major, D.[David], Lenis, D.[Dimitrios], Wimmer, M.[Maria], Berg, A.[Astrid], Neubauer, T.[Theresa], Bühler, K.[Katja],
On the Importance of Domain Awareness in Classifier Interpretations in Medical Imaging,
MedImg(42), No. 8, August 2023, pp. 2286-2298.
IEEE DOI 2308
Biomedical imaging, Solid modeling, Pathology, Deep learning, Computational modeling, Cognition, Task analysis, XAI BibRef

Lin, J.[Junfan], Wang, K.[Keze], Chen, Z.[Ziliang], Liang, X.D.[Xiao-Dan], Lin, L.[Liang],
Towards Causality-Aware Inferring: A Sequential Discriminative Approach for Medical Diagnosis,
PAMI(45), No. 11, November 2023, pp. 13363-13375.
IEEE DOI 2310
BibRef

Dong, H.Y.[Hao-Yu], Zhang, Y.F.[Yi-Fan], Gu, H.[Hanxue], Konz, N.[Nicholas], Zhang, Y.X.[Yi-Xin], Mazurowski, M.A.[Maciej A.],
SWSSL: Sliding Window-Based Self-Supervised Learning for Anomaly Detection in High-Resolution Images,
MedImg(42), No. 12, December 2023, pp. 3860-3870.
IEEE DOI 2312
BibRef

Wang, C.[Chong], Chen, Y.H.[Yuan-Hong], Liu, F.[Fengbei], Elliott, M.[Michael], Kwok, C.F.[Chun Fung], Peña-Solorzano, C.[Carlos], Frazer, H.[Helen], McCarthy, D.J.[Davis James], Carneiro, G.[Gustavo],
An Interpretable and Accurate Deep-Learning Diagnosis Framework Modeled With Fully and Semi-Supervised Reciprocal Learning,
MedImg(43), No. 1, January 2024, pp. 392-404.
IEEE DOI 2401
BibRef

Zhu, M.[Meilu], Liao, J.[Jing], Liu, J.[Jun], Yuan, Y.X.[Yi-Xuan],
FedOSS: Federated Open Set Recognition via Inter-Client Discrepancy and Collaboration,
MedImg(43), No. 1, January 2024, pp. 190-202.
IEEE DOI Code:
WWW Link. 2401
BibRef

Wang, S.L.[Shun-Li], Yang, D.K.[Ding-Kang], Zhai, P.[Peng], Zhang, L.H.[Li-Hua],
CPR-CLIP: Multimodal Pre-Training for Composite Error Recognition in CPR Training,
SPLetters(31), 2024, pp. 211-215.
IEEE DOI 2401
BibRef

Long, J.W.[Jia-Wei], Ren, J.T.[Jiang-Tao],
Interpretable multidisease diagnosis and label noise detection based on a matching network and self-paced learning,
PR(148), 2024, pp. 110178.
Elsevier DOI 2402
Multidisease diagnosis, Electronic medical record, Label noise detection, Self-paced learning, Interpretability of deep learning BibRef

Zhang, K.[Ke], Jiang, H.[Hanliang], Zhang, J.[Jian], Huang, Q.M.[Qing-Ming], Fan, J.P.[Jian-Ping], Yu, J.[Jun], Han, W.D.[Wei-Dong],
Semi-Supervised Medical Report Generation via Graph-Guided Hybrid Feature Consistency,
MultMed(26), 2024, pp. 904-915.
IEEE DOI 2402
Biomedical imaging, Pathology, Training, Semantics, Radiology, Diseases, Visualization, Knowledge graph, mean teacher, semi-supervised learning BibRef

Li, J.[Johann], Zhu, G.M.[Guang-Ming], Hua, C.[Cong], Feng, M.[Mingtao], Bennamoun, B.[Basheer], Li, P.[Ping], Lu, X.Y.[Xiao-Yuan], Song, J.[Juan], Shen, P.[Peiyi], Xu, X.[Xu], Mei, L.[Lin], Zhang, L.[Liang], Shah, S.A.A.[Syed Afaq Ali], Bennamoun, M.[Mohammed],
A Systematic Collection of Medical Image Datasets for Deep Learning,
Surveys(56), No. 5, November 2023, pp. xx-yy.
DOI Link 2402
computer-aided diagnosis, challenges, datasets, deep learning, Medical image analysis BibRef

Li, R.[Ruoting], Agor, J.K.[Joseph K.], Ozaltin, O.Y.[Osman Y.],
Temporal pattern mining for knowledge discovery in the early prediction of septic shock,
PR(151), 2024, pp. 110436.
Elsevier DOI 2404
Temporal pattern mining, Feature selection, Electronic health records, Knowledge discovery, Sepsis BibRef


Fan, J.A.[Jian-An], Liu, D.[Dongnan], Chang, H.[Hang], Huang, H.[Heng], Chen, M.[Mei], Cai, W.D.[Wei-Dong],
Taxonomy Adaptive Cross-Domain Adaptation in Medical Imaging via Optimization Trajectory Distillation,
ICCV23(21117-21127)
IEEE DOI Code:
WWW Link. 2401
Domain and data shifts. BibRef

Qiu, X.[Xihe], Shi, S.J.[Shao-Jie], Tan, X.Y.[Xiao-Yu], Qu, C.[Chao], Fang, Z.J.[Zhi-Jun], Wang, H.[Hailing], Gao, Y.B.[Yong-Bin], Wu, P.X.[Pei-Xia], Li, H.[Huawei],
Gram-based Attentive Neural Ordinary Differential Equations Network for Video Nystagmography Classification,
ICCV23(21282-21291)
IEEE DOI Code:
WWW Link. 2401
For: benign paroxysmal positional vertigo. BibRef

Cheng, P.[Pujin], Lin, L.[Li], Lyu, J.[Junyan], Huang, Y.J.[Yi-Jin], Luo, W.H.[Wen-Han], Tang, X.Y.[Xiao-Ying],
PRIOR: Prototype Representation Joint Learning from Medical Images and Reports,
ICCV23(21304-21314)
IEEE DOI Code:
WWW Link. 2401
BibRef

Fillioux, L.[Leo], Gontran, E.[Emilie], Cartry, J.[Jérôme], Mathieu, J.R.[Jacques RR], Bedja, S.[Sabrina], Boilève, A.[Alice], Cournède, P.H.[Paul-Henry], Jaulin, F.[Fanny], Christodoulidis, S.[Stergios], Vakalopoulou, M.[Maria],
Spatio-Temporal Analysis of Patient-Derived Organoid Videos Using Deep Learning for the Prediction of Drug Efficacy,
BioIm23(3932-3941)
IEEE DOI 2401
BibRef

Rao, A.[Adrit], Lee, J.Y.[Joon-Young], Aalami, O.[Oliver],
Studying the Impact of Augmentations on Medical Confidence Calibration,
CVAMD23(2454-2464)
IEEE DOI 2401
BibRef

Powers, T.[Trevor], Hatamimajoumerd, E.[Elaheh], Chu, W.[William], Rajendran, V.[Vishakk], Shah, R.[Rishi], Diabour, F.[Frank], Vaillant, M.[Marc], Fletcher, R.[Richard], Ostadabbas, S.[Sarah],
Vision-Based Treatment Localization with Limited Data: Automated Documentation of Military Emergency Medical Procedures,
ACVR23(1811-1820)
IEEE DOI 2401
BibRef

Yan, F.Y.[Fang-Yuan], Yan, B.[Bin], Pei, M.[Mingtao],
Dual Transformer Encoder Model for Medical Image Classification,
ICIP23(690-694)
IEEE DOI 2312
BibRef

Wu, F.[Fuli], Yuan, W.[Wei], Hao, P.Y.[Peng-Yi], Tian, S.Y.[Shu-Yuan],
A Structure-Fusion Network for Medical Image Classification,
ICIP23(1540-1544)
IEEE DOI 2312
BibRef

Li, M.[Meng], Li, C.Y.[Chao-Yi], Peng, C.[Can], Liu, L.C.[Liang-Chen], Lovell, B.[Brian],
End to End Generative Meta Curriculum Learning for Medical Data Augmentation,
ICIP23(2155-2159)
IEEE DOI 2312
BibRef

Huang, Y.M.[Yi-Ming], Liu, G.[Guole], Luo, Y.[Yaoru], Yang, G.[Ge],
ADFA: Attention-Augmented Differentiable Top-K Feature Adaptation for Unsupervised Medical Anomaly Detection,
ICIP23(206-210)
IEEE DOI 2312
BibRef

Che, H.X.[Hao-Xuan], Chen, S.[Siyu], Chen, H.[Hao],
Image Quality-aware Diagnosis via Meta-knowledge Co-embedding,
CVPR23(19819-19829)
IEEE DOI 2309
BibRef

Wei, Z.H.[Zheng-Hao],
Ensemble Model of Visual Transformer and CNN Helps BA Diagnosis for Doctors in Underdeveloped Areas,
ACCVWS22(73-89).
Springer DOI 2307
BibRef

Yap, B.P.[Boon Peng], Ng, B.K.[Beng Koon],
Cut-Paste Consistency Learning for Semi-Supervised Lesion Segmentation,
WACV23(6149-6158)
IEEE DOI 2302
Eye images and CT scans. Training, Image segmentation, Image analysis, Image synthesis, Computed tomography, Supervised learning, Neural networks, visual reasoning BibRef

Rodrigues, R.[Rafael], Quijano-Roy, S.[Susana], Carlier, R.Y.[Robert-Yves], Pinheiro, A.M.G.[Antonio M. G.],
Severity Classification in Cases of Collagen Vi-Related Myopathy with Convolutional Neural Networks and Handcrafted Texture Features,
ICIP22(3596-3600)
IEEE DOI 2211
Neuromuscular, Magnetic resonance imaging, Neural networks, Convolutional neural networks, Diseases. BibRef

Bhattacharya, M.[Moinak], Jain, S.[Shubham], Prasanna, P.[Prateek],
RadioTransformer: A Cascaded Global-Focal Transformer for Visual Attention-Guided Disease Classification,
ECCV22(XXI:679-698).
Springer DOI 2211
BibRef

Tao, R.S.[Ren-Shuai], Li, H.N.[Hai-Nan], Wang, T.[Tianbo], Wei, Y.[Yanlu], Ding, Y.[Yifu], Jin, B.[Bowei], Zhi, H.P.[Hong-Ping], Liu, X.L.[Xiang-Long], Liu, A.[Aishan],
Exploring Endogenous Shift for Cross-domain Detection: A Large-scale Benchmark and Perturbation Suppression Network,
CVPR22(21157-21167)
IEEE DOI 2210
Perturbation methods, Prototypes, Inspection, Benchmark testing, Hardware, Adversarial machine learning, Pattern recognition, retrieval BibRef

Paccini, M.[Martina], Patané, G.[Giuseppe], Spagnuolo, M.[Michela],
Combining Image and Geometry Processing Techniques for the Quantitative Analysis of Muscle-Skeletal Diseases,
AIRCAD22(450-461).
Springer DOI 2208
BibRef

Zhou, Y.[Yi], Huang, L.[Lei], Zhou, T.[Tao], Shao, L.[Ling],
CCT-Net: Category-Invariant Cross-Domain Transfer for Medical Single-to-Multiple Disease Diagnosis,
ICCV21(8240-8250)
IEEE DOI 2203
Heating systems, Retinopathy, Transfer learning, Semantics, Diabetes, Medical diagnosis, Task analysis, Representation learning BibRef

Chong, C.F.[Chak Fong], Yang, X.[Xu], Ke, W.[Wei], Wang, Y.P.[Ya-Peng],
GAN-based Spatial Transformation Adversarial Method for Disease Classification on CXR Photographs by Smartphones,
DICTA21(01-08)
IEEE DOI 2201
Visualization, Filtering, Image processing, Transforms, Medical services, Spatial filters, Reflection, GAN, Smartphone Photos BibRef

Abbasi, M.[Mehryar], Saeedi, P.[Parvaneh], Au, J.[Jason], Havelock, J.[Jon],
A Deep Learning Approach for Prediction of IVF Implantation Outcome from Day 3 and Day 5 Time-Lapse Human Embryo Image Sequences,
ICIP21(289-293)
IEEE DOI 2201
In vitro fertilization, Deep learning, Embryo, Protocols, Training data, Predictive models, Prediction algorithms, IVF, Embryo, Implantation BibRef

Rundo, F.[Francesco], Banna, G.L.[Giuseppe Luigi], Trenta, F.[Francesca], Battiato, S.[Sebastiano],
Advanced Deep Network with Attention and Genetic-Driven Reinforcement Learning Layer for an Efficient Cancer Treatment Outcome Prediction,
ICIP21(294-298)
IEEE DOI 2201
Image processing, Pipelines, Cancer treatment, Reinforcement learning, Clinical trials, Imaging BibRef

Wu, B.[Botong], Ren, S.[Sijie], Li, J.[Jing], Sun, X.W.[Xin-Wei], Li, S.M.[Shi-Ming], Wang, Y.Z.[Yi-Zhou],
Forecasting Irreversible Disease via Progression Learning,
CVPR21(8113-8121)
IEEE DOI 2111
Atrophy, Recurrent neural networks, Computational modeling, Predictive models, Retina, Data models BibRef

Hamdi, A.[Ali], Aboeleneen, A.[Amr], Shaban, K.[Khaled],
MARL: Multimodal Attentional Representation Learning for Disease Prediction,
CVS21(14-27).
Springer DOI 2109
BibRef

Zhang, L.[Li], Koesmahargyo, V.[Vidya], Galatzer-Levy, I.[Isaac],
Estimation of Clinical Tremor using Spatio-Temporal Adversarial AutoEncoder,
ICPR21(8259-8266)
IEEE DOI 2105
Limiting, Training data, Medical services, Predictive models, Particle measurements, Data models BibRef

Mendes, A.[Andre], Togelius, J.[Julian], dos Santos Coelho, L.[Leandro],
Adversarial Encoder-Multi-Task-Decoder for Multi-Stage Processes,
ICPR21(763-770)
IEEE DOI 2105
Training, Semisupervised learning, Decoding, Medical diagnosis, Standards, Pattern matching, multi-task, adversarial autoencoder, multi-stage BibRef

Cap, Q.H.[Quan Huu], Iyatomi, H.[Hitoshi], Fukuda, A.[Atsushi],
Miinet: An Image Quality Improvement Framework for Supporting Medical Diagnosis,
AIHA20(254-265).
Springer DOI 2103
BibRef

Huang, Y.X.[Yong-Xiang], Chung, A.C.S.[Albert C. S.],
Semi-Supervised Multimodality Learning With Graph Convolutional Neural Networks For Disease Diagnosis,
ICIP20(2451-2455)
IEEE DOI 2011
Adaptation models, Image edge detection, Imaging, Sociology, Statistics, Databases, Feature extraction, Multimodality learning, Computer-aided diagnosis BibRef

Wang, D.[Dong], Zhang, Y.[Yuan], Zhang, K.X.[Ke-Xin], Wang, L.W.[Li-Wei],
FocalMix: Semi-Supervised Learning for 3D Medical Image Detection,
CVPR20(3950-3959)
IEEE DOI 2008
Training, Task analysis, Semisupervised learning, Medical diagnostic imaging, Predictive models BibRef

Wu, B., Sun, X., Hu, L., Wang, Y.,
Learning With Unsure Data for Medical Image Diagnosis,
ICCV19(10589-10598)
IEEE DOI 2004
diseases, learning (artificial intelligence), lung, medical image processing, regression analysis, Training BibRef

Liu, X., Han, X., Qiao, Y., Ge, Y., Li, S., Lu, J.,
Unimodal-Uniform Constrained Wasserstein Training for Medical Diagnosis,
VRMI19(332-341)
IEEE DOI 2004
Task analysis, Training, Euclidean distance, Medical diagnosis, Estimation, Loss measurement, Ordinal classification, noise data BibRef

Yu, Y.[Yan], Wang, Y.Y.[Yi-Yang], Furst, J.[Jacob], Raicu, D.[Daniela],
Identifying Diagnostically Complex Cases Through Ensemble Learning,
ICIAR19(II:316-324).
Springer DOI 1909
BibRef

Liu, X.X.[Xin-Xiong], Wang, W.[Wanru],
Optimization of Proton Therapy Based on Service Design Theory,
DHM18(454-465).
Springer DOI 1807
BibRef

Carletti, M., Cristani, M., Cavedon, V., Milanese, C., Zancanaro, C., Giachetti, A.,
Analyzing Body Fat from Depth Images,
3DV18(418-425)
IEEE DOI 1812
bone, diagnostic radiography, fats, image sensors, medical image processing, regression analysis, neural networks BibRef

Shi, V.Y.X.[Vania Yu-Xi], Komiak, S.[Sherrie], Komiak, P.[Paul],
Strategies to Reduce Uncertainty on the Diagnosis Quality in the Context of Virtual Consultation: Reviews of Virtual Consultation Systems,
DHM18(527-536).
Springer DOI 1807
BibRef

Bhattacharya, I.[Indrani], Sil, J.[Jaya],
Spatial Distribution Based Provisional Disease Diagnosis in Remote Healthcare,
PReMI17(601-607).
Springer DOI 1711
BibRef

Ooi, J.Y.L.[Jodene Yen Ling], Thomas, J.J.[J. Joshua],
DengueViz: A Knowledge-Based Expert System Integrated with Parallel Coordinates Visualization in the Dengue Diagnosis,
IVIC17(50-61).
Springer DOI 1711
BibRef

Rivest-Hénault, D.[David], Ghose, S.[Soumya], Pluim, J.P.W.[Josien P.W.], Greer, P.B.[Peter B.], Fripp, J.[Jurgen], Dowling, J.A.[Jason A.],
Fast Multiatlas Selection Using Composition of Transformations for Radiation Therapy Planning,
MCV14(105-115).
Springer DOI 1501
BibRef

Lu, L.[Le], Devarakota, P.[Pandu], Vikal, S.[Siddharth], Wu, D.[Dijia], Zheng, Y.F.[Ye-Feng], Wolf, M.[Matthias],
Computer Aided Diagnosis Using Multilevel Image Features on Large-Scale Evaluation,
MCV13(161-174).
Springer DOI 1405
BibRef

Varjo, S.[Sami], Hannuksela, J.[Jari],
A Mobile Imaging System for Medical Diagnostics,
ACIVS13(215-226).
Springer DOI 1311
BibRef

Kuruvilla, A.[Anupama], Li, J.[Jian], Yeomans, P.H.[Pablo Hennings], Quelhas, P.[Pedro], Shaikh, N.[Nader], Hoberman, A.[Alejandro], Kovacevic, J.[Jelena],
Otitis media vocabulary and grammar,
ICIP12(2845-2848).
IEEE DOI 1302
diagnostic categories of otitis media BibRef

Morales, M.A.[Matías A.], Figueroa, R.L.[Rosa L.], Cabrera, J.E.[Jael E.],
Automatic Search of Nursing Diagnoses,
CIARP11(607-612).
Springer DOI 1111
BibRef

Rajendran, P., Madheswaran, M.,
Pruned Associative Classification Technique for the Medical Image Diagnosis System,
ICMV09(293-297).
IEEE DOI 0912
BibRef

Kauppi, T.[Tomi], Kamarainen, J.K.[Joni-Kristian], Lensu, L.[Lasse], Kalesnykiene, V.[Valentina], Sorri, I.[Iiris], Kälviäinen, H.[Heikki], Uusitalo, H.[Hannu], Pietilä, J.[Juhani],
Fusion of Multiple Expert Annotations and Overall Score Selection for Medical Image Diagnosis,
SCIA09(760-769).
Springer DOI 0906
BibRef

Cheaib, N.[Nader], Otmane, S.[Samir], Djemal, K.[Khalifa], Mallem, M.[Malik],
Groupware Design for Online Diagnosis Support,
IPTA08(1-7).
IEEE DOI 0811
BibRef

Spyridonos, P., Papageorgiou, E.I., Groumpos, P.P., Nikiforidis, G.N.,
Integration of Expert Knowledge and Image Analysis Techniques for Medical Diagnosis,
ICIAR06(II: 110-121).
Springer DOI 0610
BibRef

Thiran, J.P., Piscaglia, B., Piscaglia, P., Macq, B., Goudemant, J.F., Demeure, R.,
IMIS: A multi-platform software package for telediagnosis and 3D medical image processing,
ICIP96(II: 273-276).
IEEE DOI 9610
BibRef

Chapter on Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models continues in
Survival Analysis, Cancer Survival .


Last update:Apr 18, 2024 at 11:38:49