Artificial intelligence and ophthalmology : perks, perils and pitfalls / / Parul Ichhpujani, Sahil Thakur, editors |
Pubbl/distr/stampa | Singapore : , : Springer, , [2021] |
Descrizione fisica | 1 online resource (149 pages) |
Disciplina | 617.700285 |
Collana | Current Practices in Ophthalmology |
Soggetto topico |
Ophthalmology - Data processing
Artificial intelligence - Medical applications Oftalmologia Intel·ligència artificial en medicina |
Soggetto genere / forma | Llibres electrònics |
ISBN | 981-16-0634-X |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNINA-9910484596003321 |
Singapore : , : Springer, , [2021] | ||
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Lo trovi qui: Univ. Federico II | ||
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Artificial intelligence in ophthalmology / / Andrzej Grzybowski, editor |
Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
Descrizione fisica | 1 online resource (280 pages) |
Disciplina | 617.700285 |
Soggetto topico |
Ophthalmology - Data processing
Artificial intelligence - Medical applications Oftalmologia Intel·ligència artificial en medicina |
Soggetto genere / forma | Llibres electrònics |
ISBN | 3-030-78601-3 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNINA-9910502588803321 |
Cham, Switzerland : , : Springer, , [2021] | ||
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Lo trovi qui: Univ. Federico II | ||
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Computational analysis of the human eye with applications [[electronic resource] /] / Sumeet Dua, Rajendra Acharya U., E.Y.K. Ng, editors |
Pubbl/distr/stampa | Hackensack, N.J., : World Scientific, 2011 |
Descrizione fisica | 1 online resource (467 p.) |
Disciplina | 617.700285 |
Altri autori (Persone) |
DuaSumeet
Acharya URajendra NgE. Y. K |
Soggetto topico | Eye |
Soggetto genere / forma | Electronic books. |
ISBN |
1-283-23493-9
9786613234933 981-4340-30-8 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Contents; Chapter 1. The Biological and Computational Bases of Vision Hilary W. Thompson; 1.1. Introduction to the Eye; 1.2. The Anatomy of the Human Visual System; 1.3. Neurons; 1.4. Synapses; 1.5. Vision - Sensory Transduction; 1.6. Retinal Processing; 1.7. Visual Processing in the Brain; 1.8. Biological Vision and Computer Vision Algorithms; References; Chapter 2. Computational Methods for Feature Detection in Optical Images Michael Dessauer and Sumeet Dua; 2.1. Introduction to Computational Methods for Feature Detection; 2.2. Preprocessing Methods for Retinal Images
2.2.1. Illumination Effect Reduction2.2.1.1. Non-linear brightness transform; 2.2.1.2. Background identification methods; 2.2.2. Image Normalization and Enhancement; 2.2.2.1. Color channel transformations; 2.2.2.2. Image smoothing through spatial filtering; 2.2.2.3. Local adaptive contrast enhancement; 2.2.2.4. Histogram transformations; 2.3. Segmentation Methods for Retinal Anatomy Detection and Localization; 2.3.1. A Boundary Detection Methods; 2.3.1.1. First-order difference operators; 2.3.1.2. Second-order boundary detection; 2.3.1.3. Canny edge detection 2.3.2. Edge Linkage Methods for Boundary Detection2.3.2.1. Local neighborhood gradient thresholding; 2.3.2.2. Morphological operations for edge link enhancement; 2.3.2.3. Hough transform for edge linking; 2.3.3. Thresholding for Image Segmentation; 2.3.3.1. Segmentation with a single threshold; 2.3.3.2. Multi-level thresholding; 2.3.3.3. Windowed thresholding; 2.3.4. Region-Based Methods for Image Segmentation; 2.3.4.1. Region growing; 2.3.4.2. Watershed segmentation; 2.3.4.3. Matched filter segmentation; 2.4. Feature Representation Methods for Classification; 2.4.1. Statistical Features 2.4.1.1. Geometric descriptors2.4.1.2. Texture features; 2.4.1.3. Invariant moments; 2.4.2. Data Transformations; 2.4.2.1. Fourier descriptors; 2.4.2.2. Principal component analysis (PCA); 2.4.3. Multiscale Features; 2.4.3.1. Wavelet transform; 2.4.3.2. Scale-space methods for feature extraction; 2.5. Summary; References; Chapter 3. Computational Decision Support Systems and Diagnostic Tools in Ophthalmology: A Schematic Survey Sumeet Dua and Mohit Jain; 3.1. Evidence- and Value-Based Medicine; 3.1.1. EBM Process; 3.1.2. Evidence-Based Medical Issues; 3.1.3. Value-Based Evidence 3.2. Economic Evaluation of the Prevention and Treatment of Vision-Related Diseases3.2.1. Economic Evaluation; 3.2.2. Decision Analysis Method; 3.2.3. Advantages of Decision Analysis; 3.2.4. Perspective in Decision Analysis; 3.2.5. Decision Tree in Decision Analysis; 3.3. Use of Information Technologies for Diagnosis in Ophthalmology; 3.3.1. Data Mining in Ophthalmology; 3.3.2. Graphical User Interface; 3.4. Role of Computational System in Curing Disease of an Eye; 3.4.1. Computational Decision Support System: Diabetic Retinopathy; 3.4.1.1. Wavelet-based neural network23 3.4.1.2. Content-based image retrieval |
Record Nr. | UNINA-9910464514903321 |
Hackensack, N.J., : World Scientific, 2011 | ||
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Lo trovi qui: Univ. Federico II | ||
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Computational analysis of the human eye with applications / / Sumeet Dua, Rajendra Acharya U., E.Y.K. Ng, editors |
Pubbl/distr/stampa | Hackensack, N.J. : , : World Scientific, , 2011 |
Descrizione fisica | 1 online resource (467 pages) |
Disciplina | 617.700285 |
Altri autori (Persone) |
DuaSumeet
Acharya URajendra NgY. K. Eddie |
Soggetto topico | Eye |
ISBN |
1-283-23493-9
9786613234933 981-4340-30-8 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Contents; Chapter 1. The Biological and Computational Bases of Vision Hilary W. Thompson; 1.1. Introduction to the Eye; 1.2. The Anatomy of the Human Visual System; 1.3. Neurons; 1.4. Synapses; 1.5. Vision - Sensory Transduction; 1.6. Retinal Processing; 1.7. Visual Processing in the Brain; 1.8. Biological Vision and Computer Vision Algorithms; References; Chapter 2. Computational Methods for Feature Detection in Optical Images Michael Dessauer and Sumeet Dua; 2.1. Introduction to Computational Methods for Feature Detection; 2.2. Preprocessing Methods for Retinal Images
2.2.1. Illumination Effect Reduction; 2.2.1.1. Non-linear brightness transform; 2.2.1.2. Background identification methods; 2.2.2. Image Normalization and Enhancement; 2.2.2.1. Color channel transformations; 2.2.2.2. Image smoothing through spatial filtering; 2.2.2.3. Local adaptive contrast enhancement; 2.2.2.4. Histogram transformations; 2.3. Segmentation Methods for Retinal Anatomy Detection and Localization; 2.3.1. A Boundary Detection Methods; 2.3.1.1. First-order difference operators; 2.3.1.2. Second-order boundary detection; 2.3.1.3. Canny edge detection 2.3.2. Edge Linkage Methods for Boundary Detection; 2.3.2.1. Local neighborhood gradient thresholding; 2.3.2.2. Morphological operations for edge link enhancement; 2.3.2.3. Hough transform for edge linking; 2.3.3. Thresholding for Image Segmentation; 2.3.3.1. Segmentation with a single threshold; 2.3.3.2. Multi-level thresholding; 2.3.3.3. Windowed thresholding; 2.3.4. Region-Based Methods for Image Segmentation; 2.3.4.1. Region growing; 2.3.4.2. Watershed segmentation; 2.3.4.3. Matched filter segmentation; 2.4. Feature Representation Methods for Classification; 2.4.1. Statistical Features 2.4.1.1. Geometric descriptors; 2.4.1.2. Texture features; 2.4.1.3. Invariant moments; 2.4.2. Data Transformations; 2.4.2.1. Fourier descriptors; 2.4.2.2. Principal component analysis (PCA); 2.4.3. Multiscale Features; 2.4.3.1. Wavelet transform; 2.4.3.2. Scale-space methods for feature extraction; 2.5. Summary; References; Chapter 3. Computational Decision Support Systems and Diagnostic Tools in Ophthalmology: A Schematic Survey Sumeet Dua and Mohit Jain; 3.1. Evidence- and Value-Based Medicine; 3.1.1. EBM Process; 3.1.2. Evidence-Based Medical Issues; 3.1.3. Value-Based Evidence 3.2. Economic Evaluation of the Prevention and Treatment of Vision-Related Diseases; 3.2.1. Economic Evaluation; 3.2.2. Decision Analysis Method; 3.2.3. Advantages of Decision Analysis; 3.2.4. Perspective in Decision Analysis; 3.2.5. Decision Tree in Decision Analysis; 3.3. Use of Information Technologies for Diagnosis in Ophthalmology; 3.3.1. Data Mining in Ophthalmology; 3.3.2. Graphical User Interface; 3.4. Role of Computational System in Curing Disease of an Eye; 3.4.1. Computational Decision Support System: Diabetic Retinopathy; 3.4.1.1. Wavelet-based neural network23; .4.1.2. Content-based image retrieval |
Record Nr. | UNINA-9910789064003321 |
Hackensack, N.J. : , : World Scientific, , 2011 | ||
![]() | ||
Lo trovi qui: Univ. Federico II | ||
|
Computational analysis of the human eye with applications / / Sumeet Dua, Rajendra Acharya U., E.Y.K. Ng, editors |
Pubbl/distr/stampa | Hackensack, N.J. : , : World Scientific, , 2011 |
Descrizione fisica | 1 online resource (467 pages) |
Disciplina | 617.700285 |
Altri autori (Persone) |
DuaSumeet
Acharya URajendra NgY. K. Eddie |
Soggetto topico | Eye |
ISBN |
1-283-23493-9
9786613234933 981-4340-30-8 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Contents; Chapter 1. The Biological and Computational Bases of Vision Hilary W. Thompson; 1.1. Introduction to the Eye; 1.2. The Anatomy of the Human Visual System; 1.3. Neurons; 1.4. Synapses; 1.5. Vision - Sensory Transduction; 1.6. Retinal Processing; 1.7. Visual Processing in the Brain; 1.8. Biological Vision and Computer Vision Algorithms; References; Chapter 2. Computational Methods for Feature Detection in Optical Images Michael Dessauer and Sumeet Dua; 2.1. Introduction to Computational Methods for Feature Detection; 2.2. Preprocessing Methods for Retinal Images
2.2.1. Illumination Effect Reduction; 2.2.1.1. Non-linear brightness transform; 2.2.1.2. Background identification methods; 2.2.2. Image Normalization and Enhancement; 2.2.2.1. Color channel transformations; 2.2.2.2. Image smoothing through spatial filtering; 2.2.2.3. Local adaptive contrast enhancement; 2.2.2.4. Histogram transformations; 2.3. Segmentation Methods for Retinal Anatomy Detection and Localization; 2.3.1. A Boundary Detection Methods; 2.3.1.1. First-order difference operators; 2.3.1.2. Second-order boundary detection; 2.3.1.3. Canny edge detection 2.3.2. Edge Linkage Methods for Boundary Detection; 2.3.2.1. Local neighborhood gradient thresholding; 2.3.2.2. Morphological operations for edge link enhancement; 2.3.2.3. Hough transform for edge linking; 2.3.3. Thresholding for Image Segmentation; 2.3.3.1. Segmentation with a single threshold; 2.3.3.2. Multi-level thresholding; 2.3.3.3. Windowed thresholding; 2.3.4. Region-Based Methods for Image Segmentation; 2.3.4.1. Region growing; 2.3.4.2. Watershed segmentation; 2.3.4.3. Matched filter segmentation; 2.4. Feature Representation Methods for Classification; 2.4.1. Statistical Features 2.4.1.1. Geometric descriptors; 2.4.1.2. Texture features; 2.4.1.3. Invariant moments; 2.4.2. Data Transformations; 2.4.2.1. Fourier descriptors; 2.4.2.2. Principal component analysis (PCA); 2.4.3. Multiscale Features; 2.4.3.1. Wavelet transform; 2.4.3.2. Scale-space methods for feature extraction; 2.5. Summary; References; Chapter 3. Computational Decision Support Systems and Diagnostic Tools in Ophthalmology: A Schematic Survey Sumeet Dua and Mohit Jain; 3.1. Evidence- and Value-Based Medicine; 3.1.1. EBM Process; 3.1.2. Evidence-Based Medical Issues; 3.1.3. Value-Based Evidence 3.2. Economic Evaluation of the Prevention and Treatment of Vision-Related Diseases; 3.2.1. Economic Evaluation; 3.2.2. Decision Analysis Method; 3.2.3. Advantages of Decision Analysis; 3.2.4. Perspective in Decision Analysis; 3.2.5. Decision Tree in Decision Analysis; 3.3. Use of Information Technologies for Diagnosis in Ophthalmology; 3.3.1. Data Mining in Ophthalmology; 3.3.2. Graphical User Interface; 3.4. Role of Computational System in Curing Disease of an Eye; 3.4.1. Computational Decision Support System: Diabetic Retinopathy; 3.4.1.1. Wavelet-based neural network23; .4.1.2. Content-based image retrieval |
Record Nr. | UNINA-9910812390803321 |
Hackensack, N.J. : , : World Scientific, , 2011 | ||
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Lo trovi qui: Univ. Federico II | ||
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