Info
Computational Mathematics Modeling in Cancer Analysis : First International Workshop, CMMCA 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18, 2022, Proceedings / / edited by Wenjian Qin, Nazar Zaki, Fa Zhang, Jia Wu, Fan Yang
| Computational Mathematics Modeling in Cancer Analysis : First International Workshop, CMMCA 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18, 2022, Proceedings / / edited by Wenjian Qin, Nazar Zaki, Fa Zhang, Jia Wu, Fan Yang |
| Edizione | [1st ed. 2022.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2022 |
| Descrizione fisica | 1 online resource (171 pages) |
| Disciplina |
636.80896994
616.99400113 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Image processing - Digital techniques
Computer vision Computer engineering Computer networks Machine learning Computers Computer Imaging, Vision, Pattern Recognition and Graphics Computer Engineering and Networks Machine Learning Computing Milieux |
| ISBN |
9783031172663
3031172663 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Cellular Architecture on Whole Slide Images Allows the Prediction of Survival in Lung Adenocarcinoma -- Is More Always Better? Effects of Patch Sampling in Distinguishing Chronic Lymphocytic Leukemia from Transformation to Diffuse Large B-cell Lymphoma -- Repeatability of Radiomic Features against Simulated Scanning Position Stochasticity across Imaging Modalities and Cancer Subtypes: A Retrospective Multi-Institutional Study on Head-and-Neck Cases -- MLCN: Metric Learning Constrained Network for Whole Slide Image Classification with Bilinear Gated Attention Mechanism -- NucDETR: End-to-End Transformer for Nucleus Detection in Histopathology Images -- Self-supervised learning based on a pre-trained method for the subtype classification of spinal tumors -- CanDLE: Illuminating Biases in Transcriptomic Pan-Cancer Diagnosis -- Cross-Stream Interactions: Segmentation of Lung Adenocarcinoma Growth Patterns -- Modality-collaborative AI model Ensemble for Lung Cancer Early Diagnosis -- Clustering-based Multi-instance Learning Network for Whole Slide Image Classification -- Multi-task Learning-driven Volume and Slice Level Contrastive Learning for 3D Medical Image Classification -- Light Annotation Fine Segmentation: Histology Image Segmentation based on VGG Fusion with Global Normalisation CAM -- Tubular Structure-Aware Convolutional Neural Networks for Organ at Risks Segmentation in Cervical Cancer Radiotherapy -- Automatic Computer-aided Histopathologic Segmentation for Nasopharyngeal Carcinoma using Transformer Framework -- Accurate Breast Tumor Identification UsingComputational Ultrasound Image Features. |
| Record Nr. | UNINA-9910595023903321 |
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Mathematical models of cancer and different therapies : unified framework / / Regina Padmanabhan, Nader Meskin, Ala-Eddin Al Moustafa
| Mathematical models of cancer and different therapies : unified framework / / Regina Padmanabhan, Nader Meskin, Ala-Eddin Al Moustafa |
| Autore | Padmanabhan Regina |
| Edizione | [1st ed. 2021.] |
| Pubbl/distr/stampa | Gateway East, Singapore : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (XVI, 256 p. 35 illus., 29 illus. in color.) |
| Disciplina | 616.99400113 |
| Collana | Series in BioEngineering |
| Soggetto topico | Cancer - Mathematical models |
| ISBN | 981-15-8640-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Background -- Time series data to mathematical model -- Chemotherapy models -- Immunotherapy models -- Anti-angiogenic therapy models -- Radiotherapy Models -- Hormone therapy models -- Miscellaneous therapy models -- Combination therapy models -- Control stratergies used for cancer therapy -- Conclusions. |
| Record Nr. | UNINA-9910483024703321 |
Padmanabhan Regina
|
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| Gateway East, Singapore : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Mathematical Models of Cancer and Different Therapies : Unified Framework / / by Regina Padmanabhan, Nader Meskin, Ala-Eddin Al Moustafa
| Mathematical Models of Cancer and Different Therapies : Unified Framework / / by Regina Padmanabhan, Nader Meskin, Ala-Eddin Al Moustafa |
| Autore | Padmanabhan Regina |
| Edizione | [1st ed. 2021.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2021 |
| Descrizione fisica | 1 online resource (xvi, 256 pages) : ilustrations |
| Disciplina | 616.99400113 |
| Collana | Series in BioEngineering |
| Soggetto topico |
Biomedical engineering
Biomathematics Cancer Biomedical Engineering and Bioengineering Mathematical and Computational Biology Cancer Biology |
| ISBN |
9789811586408
9811586403 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Background -- Time series data to mathematical model -- Chemotherapy models -- Immunotherapy models -- Anti-angiogenic therapy models -- Radiotherapy Models -- Hormone therapy models -- Miscellaneous therapy models -- Combination therapy models -- Control stratergies used for cancer therapy -- Conclusions. |
| Record Nr. | UNINA-9910863283603321 |
|
Padmanabhan Regina
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| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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