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Biblioteca

MARC Lista (tabellare)
The Biological and Clinical Aspects of Merkel Cell Carcinoma / / edited by Virve Koljonen, Weng-Onn Lui and Jürgen Becker
The Biological and Clinical Aspects of Merkel Cell Carcinoma / / edited by Virve Koljonen, Weng-Onn Lui and Jürgen Becker
Pubbl/distr/stampa [Place of publication not identified] : , : MDPI - Multidisciplinary Digital Publishing Institute, , 2023
Descrizione fisica 1 online resource
Disciplina 616.99461
Soggetto topico Life (Biology)
Life sciences
Carcinoma, Renal Cell
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910734354803321
[Place of publication not identified] : , : MDPI - Multidisciplinary Digital Publishing Institute, , 2023
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Clear Cell Renal Cell Carcinoma 2021-2022 / / Claudia Manini and José I. López
Clear Cell Renal Cell Carcinoma 2021-2022 / / Claudia Manini and José I. López
Autore Manini Claudia
Pubbl/distr/stampa Basel, Switzerland : , : MDPI - Multidisciplinary Digital Publishing Institute, , 2022
Descrizione fisica 1 online resource (342 pages)
Disciplina 616.99461
Soggetto topico Biomedical materials
Carcinoma, Renal Cell
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910674386903321
Manini Claudia  
Basel, Switzerland : , : MDPI - Multidisciplinary Digital Publishing Institute, , 2022
Materiale a stampa
Lo trovi qui: Univ. Federico II
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Emerging research and treatments in renal cell carcinoma / / edited by Robert J. Amato
Emerging research and treatments in renal cell carcinoma / / edited by Robert J. Amato
Pubbl/distr/stampa Rijeka, Croatia : , : IntechOpen, , [2012]
Descrizione fisica 1 online resource (454 pages) : illustrations
Disciplina 616.99461
Soggetto topico Renal cell carcinoma
ISBN 953-51-6803-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910317650703321
Rijeka, Croatia : , : IntechOpen, , [2012]
Materiale a stampa
Lo trovi qui: Univ. Federico II
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A Guide to Management of Urological Cancers / / edited by Prabhjot Singh, Brusabhanu Nayak, Sridhar Panaiyadiyan
A Guide to Management of Urological Cancers / / edited by Prabhjot Singh, Brusabhanu Nayak, Sridhar Panaiyadiyan
Autore Singh Prabhjot
Edizione [1st ed. 2023.]
Pubbl/distr/stampa Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023
Descrizione fisica 1 online resource (364 pages)
Disciplina 616.99461
Altri autori (Persone) NayakBrusabhanu
PanaiyadiyanSridhar
Soggetto topico Oncology
Urology
Genitourinary organs - Surgery
Urological Surgery
ISBN 981-9923-41-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Diagnosis and clinical staging -- Management -- Pathological staging -- Adjuvant treatment and follow-up -- Diagnosis and clinical staging -- Management -- Pathological staging -- Adjuvant treatment and follow-up.
Record Nr. UNINA-9910747593003321
Singh Prabhjot  
Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023
Materiale a stampa
Lo trovi qui: Univ. Federico II
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Innovations in nephrology : breakthrough technologies in kidney disease care / / edited by Geraldo Bezerra da Silva and Masaomi Nangaku
Innovations in nephrology : breakthrough technologies in kidney disease care / / edited by Geraldo Bezerra da Silva and Masaomi Nangaku
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2022]
Descrizione fisica 1 online resource (538 pages)
Disciplina 616.99461
Soggetto topico Nephrology
Kidneys - Displacement
ISBN 3-031-11570-8
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910624377403321
Cham, Switzerland : , : Springer, , [2022]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Kidney and kidney tumor segmentation : MICCAI 2021 Challenge, KiTS 2021, held in conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021, proceedings / / edited by Nicholas Heller, [and five others]
Kidney and kidney tumor segmentation : MICCAI 2021 Challenge, KiTS 2021, held in conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021, proceedings / / edited by Nicholas Heller, [and five others]
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2022]
Descrizione fisica 1 online resource (173 pages)
Disciplina 616.99461
Collana Lecture Notes in Computer Science
Soggetto topico Electronic data processing
Punched card systems
ISBN 3-030-98385-4
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Contents -- Automated Kidney Tumor Segmentation with Convolution and Transformer Network -- 1 Introduction -- 2 Related Work -- 2.1 Medical Image Segmentation -- 2.2 Self-attention Mechanism -- 3 Methods -- 3.1 Network Architecture -- 3.2 Loss Function -- 3.3 Pre- and post- processing -- 3.4 Implementation Details -- 4 Results -- 4.1 Dataset -- 4.2 Metrics -- 4.3 Results on KITS21 Training Set -- 4.4 Results on KITS21 Test Set -- 5 Discussion and Conclusion -- References -- Extraction of Kidney Anatomy Based on a 3D U-ResNet with Overlap-Tile Strategy -- 1 Introduction -- 2 Methods -- 2.1 Training and Validation Data -- 2.2 Preprocessing -- 2.3 Proposed Method -- 2.4 Postprocessing -- 3 Results -- 4 Discussion and Conclusion -- References -- Modified nnU-Net for the MICCAI KiTS21 Challenge -- 1 Introduction -- 2 Methods -- 2.1 Training and Validation Data -- 2.2 Preprocessing -- 2.3 Proposed Method -- 3 Results -- 4 Discussion and Conclusion -- References -- 2.5D Cascaded Semantic Segmentation for Kidney Tumor Cyst -- 1 Introduction -- 2 Methods -- 2.1 Training and Validation Data -- 2.2 Preprocessing -- 2.3 Proposed Method -- 3 Results -- 4 Discussion and Conclusion -- References -- Automated Machine Learning Algorithm for Kidney, Kidney Tumor, Kidney Cyst Segmentation in Computed Tomography Scans -- 1 Introduction -- 2 Methods -- 2.1 Training and Validation Data -- 2.2 Preprocessing -- 2.3 Network Architecture -- 2.4 Network Training -- 3 Results -- 4 Discussion and Conclusion -- References -- Three Uses of One Neural Network: Automatic Segmentation of Kidney Tumor and Cysts Based on 3D U-Net -- 1 Introduction -- 2 Methods -- 2.1 Network Architecture -- 2.2 Segmentation from Low-Resolution CT -- 2.3 Fine Segmentation of Kidney -- 2.4 Segmentation of Tumor and Cysts -- 2.5 Training Protocols -- 3 Results.
4 Discussion and Conclusion -- References -- Less is More: Contrast Attention Assisted U-Net for Kidney, Tumor and Cyst Segmentations -- 1 Introduction -- 2 Methods -- 2.1 Training and Validation Data -- 2.2 Preprocessing -- 2.3 Proposed Network Architecture -- 3 Results -- 4 Discussion and Conclusion -- References -- A Coarse-to-Fine Framework for the 2021 Kidney and Kidney Tumor Segmentation Challenge -- 1 Introduction -- 2 Methods -- 2.1 Training and Validation Data -- 2.2 Preprocessing -- 2.3 Proposed Method -- 3 Results -- 3.1 Metric -- 3.2 Results and Discussions -- 4 Conclusion -- References -- Kidney and Kidney Tumor Segmentation Using a Two-Stage Cascade Framework -- 1 Introduction -- 2 Methods -- 2.1 Kidney-Net -- 2.2 Masses-Net -- 2.3 Loss Function -- 3 Experiment -- 3.1 Datasets -- 3.2 Pre-processing and Post-processing -- 3.3 Training and Implementation Details -- 3.4 Metrics -- 4 Results and Discussion -- 5 Conclusion -- References -- Squeeze-and-Excitation Encoder-Decoder Network for Kidney and Kidney Tumor Segmentation in CT Images -- 1 Introduction -- 2 Method -- 2.1 Architecture -- 2.2 Squeeze-and-Excitation Module -- 2.3 Deep Supervision -- 2.4 Loss Function -- 3 Experiments -- 3.1 Datasets -- 3.2 Metrics -- 3.3 Pre- and Post-processing -- 3.4 Implementation Details -- 4 Result -- 5 Discussion and Conclusion -- References -- A Two-Stage Cascaded Deep Neural Network with Multi-decoding Paths for Kidney Tumor Segmentation -- 1 Introduction -- 2 Methods -- 2.1 Kidney Localization Network -- 2.2 Multi-decoding Segmentation Network -- 2.3 Global Context Fusion Block -- 2.4 Regional Constraint Loss Function -- 3 Experimental Results -- 3.1 Dataset -- 3.2 Implementation Details -- 3.3 Results -- 4 Conclusion -- References -- Mixup Augmentation for Kidney and Kidney Tumor Segmentation -- 1 Introduction -- 2 Methods.
2.1 Training and Validation Data -- 2.2 Preprocessing -- 2.3 Proposed Method -- 3 Results -- 4 Discussion -- References -- Automatic Segmentation in Abdominal CT Imaging for the KiTS21 Challenge -- 1 Introduction -- 2 Methods -- 2.1 Training and Validation Data -- 2.2 Preprocessing -- 2.3 Proposed Method -- 3 Results -- 4 Discussion and Conclusion -- References -- An Ensemble of 3D U-Net Based Models for Segmentation of Kidney and Masses in CT Scans -- 1 Introduction -- 2 nnU-Net Determined Details -- 2.1 3D U-Net Network Architecture -- 2.2 3D U-Net Cascade Network Architecture -- 2.3 Preprocessing -- 2.4 Training Details -- 3 Method -- 3.1 Training and Validation Data -- 3.2 Pretraining -- 3.3 Annotations -- 3.4 Regularized Loss -- 3.5 Postprocessing -- 3.6 Final Submission -- 4 Results -- 4.1 Single-Stage, High-Resolution 3D U-Net -- 4.2 3D U-Net Cascade -- 4.3 Model Ensemble -- 4.4 Postprocessing -- 4.5 Test Set Results -- 5 Discussion and Conclusions -- References -- Contrast-Enhanced CT Renal Tumor Segmentation -- 1 Introduction -- 2 Methods -- 2.1 Training and Validation Data -- 2.2 Preprocessing -- 2.3 Proposed Method -- 3 Results -- 4 Discussion and Conclusion -- References -- A Cascaded 3D Segmentation Model for Renal Enhanced CT Images -- 1 Introduction -- 2 Methods -- 2.1 Training and Validation Data -- 2.2 Preprocessing -- 2.3 Proposed Method -- 3 Results -- 4 Discussion and Conclusion -- References -- Leveraging Clinical Characteristics for Improved Deep Learning-Based Kidney Tumor Segmentation on CT -- 1 Introduction -- 2 Materials and Methods -- 2.1 Training and Validation Data -- 2.2 Preprocessing -- 2.3 Baseline 3D U-Net -- 2.4 Cognizant Sampling Leveraging Clinical Characteristics -- 2.5 Statistical Evaluation -- 3 Results -- 4 Discussion and Conclusion -- References.
A Coarse-to-Fine 3D U-Net Network for Semantic Segmentation of Kidney CT Scans -- 1 Introduction -- 2 Methods -- 2.1 Training and Validation Data -- 2.2 Data Preprocessing -- 2.3 Proposed Method -- 3 Results -- 4 Discussion and Conclusion -- References -- 3D U-Net Based Semantic Segmentation of Kidneys and Renal Masses on Contrast-Enhanced CT -- 1 Introduction -- 2 Methods -- 2.1 Training and Validation Data -- 2.2 Preprocessing -- 2.3 Network Architecture -- 2.4 Loss Function -- 2.5 Optimization Strategy -- 2.6 Validation -- 2.7 Post-processing -- 3 Results -- 4 Discussion and Conclusion -- References -- Kidney and Kidney Tumor Segmentation Using Spatial and Channel Attention Enhanced U-Net -- 1 Introduction -- 2 Methods -- 2.1 Training and Validation Data -- 2.2 Preprocessing -- 2.3 Data Augmentations -- 2.4 Proposed Method -- 2.5 Residual U-Net for Comparison -- 2.6 Implementation and Training -- 2.7 Inference Procedure -- 3 Results -- 4 Conclusion -- References -- Transfer Learning for KiTS21 Challenge -- 1 Introduction -- 2 Methods -- 2.1 Training and Validation Data -- 2.2 Preprocessing -- 2.3 Proposed Method -- 3 Results -- 4 Discussion and Conclusion -- References -- Author Index.
Record Nr. UNISA-996464542303316
Cham, Switzerland : , : Springer, , [2022]
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Kidney and kidney tumor segmentation : MICCAI 2021 Challenge, KiTS 2021, held in conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021, proceedings / / edited by Nicholas Heller, [and five others]
Kidney and kidney tumor segmentation : MICCAI 2021 Challenge, KiTS 2021, held in conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021, proceedings / / edited by Nicholas Heller, [and five others]
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2022]
Descrizione fisica 1 online resource (173 pages)
Disciplina 616.99461
Collana Lecture Notes in Computer Science
Soggetto topico Electronic data processing
Punched card systems
ISBN 3-030-98385-4
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Organization -- Contents -- Automated Kidney Tumor Segmentation with Convolution and Transformer Network -- 1 Introduction -- 2 Related Work -- 2.1 Medical Image Segmentation -- 2.2 Self-attention Mechanism -- 3 Methods -- 3.1 Network Architecture -- 3.2 Loss Function -- 3.3 Pre- and post- processing -- 3.4 Implementation Details -- 4 Results -- 4.1 Dataset -- 4.2 Metrics -- 4.3 Results on KITS21 Training Set -- 4.4 Results on KITS21 Test Set -- 5 Discussion and Conclusion -- References -- Extraction of Kidney Anatomy Based on a 3D U-ResNet with Overlap-Tile Strategy -- 1 Introduction -- 2 Methods -- 2.1 Training and Validation Data -- 2.2 Preprocessing -- 2.3 Proposed Method -- 2.4 Postprocessing -- 3 Results -- 4 Discussion and Conclusion -- References -- Modified nnU-Net for the MICCAI KiTS21 Challenge -- 1 Introduction -- 2 Methods -- 2.1 Training and Validation Data -- 2.2 Preprocessing -- 2.3 Proposed Method -- 3 Results -- 4 Discussion and Conclusion -- References -- 2.5D Cascaded Semantic Segmentation for Kidney Tumor Cyst -- 1 Introduction -- 2 Methods -- 2.1 Training and Validation Data -- 2.2 Preprocessing -- 2.3 Proposed Method -- 3 Results -- 4 Discussion and Conclusion -- References -- Automated Machine Learning Algorithm for Kidney, Kidney Tumor, Kidney Cyst Segmentation in Computed Tomography Scans -- 1 Introduction -- 2 Methods -- 2.1 Training and Validation Data -- 2.2 Preprocessing -- 2.3 Network Architecture -- 2.4 Network Training -- 3 Results -- 4 Discussion and Conclusion -- References -- Three Uses of One Neural Network: Automatic Segmentation of Kidney Tumor and Cysts Based on 3D U-Net -- 1 Introduction -- 2 Methods -- 2.1 Network Architecture -- 2.2 Segmentation from Low-Resolution CT -- 2.3 Fine Segmentation of Kidney -- 2.4 Segmentation of Tumor and Cysts -- 2.5 Training Protocols -- 3 Results.
4 Discussion and Conclusion -- References -- Less is More: Contrast Attention Assisted U-Net for Kidney, Tumor and Cyst Segmentations -- 1 Introduction -- 2 Methods -- 2.1 Training and Validation Data -- 2.2 Preprocessing -- 2.3 Proposed Network Architecture -- 3 Results -- 4 Discussion and Conclusion -- References -- A Coarse-to-Fine Framework for the 2021 Kidney and Kidney Tumor Segmentation Challenge -- 1 Introduction -- 2 Methods -- 2.1 Training and Validation Data -- 2.2 Preprocessing -- 2.3 Proposed Method -- 3 Results -- 3.1 Metric -- 3.2 Results and Discussions -- 4 Conclusion -- References -- Kidney and Kidney Tumor Segmentation Using a Two-Stage Cascade Framework -- 1 Introduction -- 2 Methods -- 2.1 Kidney-Net -- 2.2 Masses-Net -- 2.3 Loss Function -- 3 Experiment -- 3.1 Datasets -- 3.2 Pre-processing and Post-processing -- 3.3 Training and Implementation Details -- 3.4 Metrics -- 4 Results and Discussion -- 5 Conclusion -- References -- Squeeze-and-Excitation Encoder-Decoder Network for Kidney and Kidney Tumor Segmentation in CT Images -- 1 Introduction -- 2 Method -- 2.1 Architecture -- 2.2 Squeeze-and-Excitation Module -- 2.3 Deep Supervision -- 2.4 Loss Function -- 3 Experiments -- 3.1 Datasets -- 3.2 Metrics -- 3.3 Pre- and Post-processing -- 3.4 Implementation Details -- 4 Result -- 5 Discussion and Conclusion -- References -- A Two-Stage Cascaded Deep Neural Network with Multi-decoding Paths for Kidney Tumor Segmentation -- 1 Introduction -- 2 Methods -- 2.1 Kidney Localization Network -- 2.2 Multi-decoding Segmentation Network -- 2.3 Global Context Fusion Block -- 2.4 Regional Constraint Loss Function -- 3 Experimental Results -- 3.1 Dataset -- 3.2 Implementation Details -- 3.3 Results -- 4 Conclusion -- References -- Mixup Augmentation for Kidney and Kidney Tumor Segmentation -- 1 Introduction -- 2 Methods.
2.1 Training and Validation Data -- 2.2 Preprocessing -- 2.3 Proposed Method -- 3 Results -- 4 Discussion -- References -- Automatic Segmentation in Abdominal CT Imaging for the KiTS21 Challenge -- 1 Introduction -- 2 Methods -- 2.1 Training and Validation Data -- 2.2 Preprocessing -- 2.3 Proposed Method -- 3 Results -- 4 Discussion and Conclusion -- References -- An Ensemble of 3D U-Net Based Models for Segmentation of Kidney and Masses in CT Scans -- 1 Introduction -- 2 nnU-Net Determined Details -- 2.1 3D U-Net Network Architecture -- 2.2 3D U-Net Cascade Network Architecture -- 2.3 Preprocessing -- 2.4 Training Details -- 3 Method -- 3.1 Training and Validation Data -- 3.2 Pretraining -- 3.3 Annotations -- 3.4 Regularized Loss -- 3.5 Postprocessing -- 3.6 Final Submission -- 4 Results -- 4.1 Single-Stage, High-Resolution 3D U-Net -- 4.2 3D U-Net Cascade -- 4.3 Model Ensemble -- 4.4 Postprocessing -- 4.5 Test Set Results -- 5 Discussion and Conclusions -- References -- Contrast-Enhanced CT Renal Tumor Segmentation -- 1 Introduction -- 2 Methods -- 2.1 Training and Validation Data -- 2.2 Preprocessing -- 2.3 Proposed Method -- 3 Results -- 4 Discussion and Conclusion -- References -- A Cascaded 3D Segmentation Model for Renal Enhanced CT Images -- 1 Introduction -- 2 Methods -- 2.1 Training and Validation Data -- 2.2 Preprocessing -- 2.3 Proposed Method -- 3 Results -- 4 Discussion and Conclusion -- References -- Leveraging Clinical Characteristics for Improved Deep Learning-Based Kidney Tumor Segmentation on CT -- 1 Introduction -- 2 Materials and Methods -- 2.1 Training and Validation Data -- 2.2 Preprocessing -- 2.3 Baseline 3D U-Net -- 2.4 Cognizant Sampling Leveraging Clinical Characteristics -- 2.5 Statistical Evaluation -- 3 Results -- 4 Discussion and Conclusion -- References.
A Coarse-to-Fine 3D U-Net Network for Semantic Segmentation of Kidney CT Scans -- 1 Introduction -- 2 Methods -- 2.1 Training and Validation Data -- 2.2 Data Preprocessing -- 2.3 Proposed Method -- 3 Results -- 4 Discussion and Conclusion -- References -- 3D U-Net Based Semantic Segmentation of Kidneys and Renal Masses on Contrast-Enhanced CT -- 1 Introduction -- 2 Methods -- 2.1 Training and Validation Data -- 2.2 Preprocessing -- 2.3 Network Architecture -- 2.4 Loss Function -- 2.5 Optimization Strategy -- 2.6 Validation -- 2.7 Post-processing -- 3 Results -- 4 Discussion and Conclusion -- References -- Kidney and Kidney Tumor Segmentation Using Spatial and Channel Attention Enhanced U-Net -- 1 Introduction -- 2 Methods -- 2.1 Training and Validation Data -- 2.2 Preprocessing -- 2.3 Data Augmentations -- 2.4 Proposed Method -- 2.5 Residual U-Net for Comparison -- 2.6 Implementation and Training -- 2.7 Inference Procedure -- 3 Results -- 4 Conclusion -- References -- Transfer Learning for KiTS21 Challenge -- 1 Introduction -- 2 Methods -- 2.1 Training and Validation Data -- 2.2 Preprocessing -- 2.3 Proposed Method -- 3 Results -- 4 Discussion and Conclusion -- References -- Author Index.
Record Nr. UNINA-9910556885903321
Cham, Switzerland : , : Springer, , [2022]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Kidney cancer : recent advances in surgical and molecular pathology / / edited by Mukul K. Divatia, Ayhan Ozcan, Charles C. Guo, Jae Y. Ro
Kidney cancer : recent advances in surgical and molecular pathology / / edited by Mukul K. Divatia, Ayhan Ozcan, Charles C. Guo, Jae Y. Ro
Edizione [1st ed. 2020.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020
Descrizione fisica 1 online resource (xi, 445 pages)
Disciplina 616.07
616.99461
Soggetto topico Kidneys - Cancer - Molecular aspects
Surgical oncology
Interventional radiology 
Pathology
Urology
Surgical Oncology
Interventional Radiology
ISBN 3-030-28333-X
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Surgical Considerations in Renal Tumors -- Renal Cell Carcinoma: The Oncologist’s Point of View -- Normal Anatomy and Histology of the Kidney: Importance for Kidney Tumors -- Benign Renal Epithelial / Epithelial and Stromal Tumors -- Major Subtypes of Renal Cell Carcinoma -- New and Emerging Subtypes of Renal Cell Carcinoma -- Renal Mass Biopsy -- Mesenchymal Kidney Tumors -- Pediatric Renal Tumors: Diagnostic Updates -- Neuroendocrine Kidney Tumors -- Hereditary Syndromes Associated with Kidney Tumors -- Lymphoid Neoplasms of the Kidney -- Tumors of the Renal Pelvis -- Non-Neoplastic Changes in Nephrectomy Specimens for Tumors -- Application of Immunohistochemistry in Diagnosis of Renal Cell Neoplasms -- Cytology of Kidney Tumors -- Diagnostic Imaging in Renal Tumors. Molecular Pathology of Kidney Tumors -- Targeted Treatment of Renal Cell Carcinoma -- Specimen Handling: Radical and Partial Nephrectomy Specimens -- Staging and Reporting of Renal Cell Carcinomas.
Record Nr. UNINA-9910369953603321
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Management of urological cancers in older people / / Jean-Pierre Droz, Riccardo A. Audisio, editors ; Riccardo A. Audisio, series editor
Management of urological cancers in older people / / Jean-Pierre Droz, Riccardo A. Audisio, editors ; Riccardo A. Audisio, series editor
Autore Droz Jean-Pierre
Edizione [1st ed. 2013.]
Pubbl/distr/stampa London, : Springer, 2013
Descrizione fisica 1 online resource (366 p.)
Disciplina 616.9946
616.99461
Altri autori (Persone) AudisioRiccardo A
Collana Management of cancer in older people
Soggetto topico Genitourinary organs - Cancer
Geriatric oncology
ISBN 0-85729-999-9
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto pt. 1. Background and epidemiology -- pt. 2. Prostate cancer : general considerations -- pt. 3. Prostate cancer : localized disease -- pt. 4. Prostate cancer : metastatic disease -- pt. 5. Bladder cancer -- pt. 6. Renal cancer -- pt. 7. Rare cancers.
Record Nr. UNINA-9910438019603321
Droz Jean-Pierre  
London, : Springer, 2013
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Principles and Practice of Urooncology : Radiotherapy, Surgery and Systemic Therapy / / edited by Gokhan Ozyigit, Ugur Selek
Principles and Practice of Urooncology : Radiotherapy, Surgery and Systemic Therapy / / edited by Gokhan Ozyigit, Ugur Selek
Edizione [1st ed. 2017.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017
Descrizione fisica 1 online resource (445 pages) : illustrations (some color)
Disciplina 616.99461
Soggetto topico Radiotherapy
Oncology  
Urology
Oncology
ISBN 3-319-56114-6
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Selection criteria based on Radiation Oncology perspective for definitive treatment approaches in urological cancers -- Radiological imaging in urological cancers -- The role of functional imaging in urological cancers -- Surgery in renal cell cancer -- Systemic therapies in renal cell cancer -- The role of radiotherapy in renal cell cancer -- Screening of prostate cancer: Pros and Cons -- Risk groupings in prostate cancer -- Active surveillance in low risk cancer: Pros and Cons -- Alternative focal therapies in low-risk prostate cancer: HiFU and Cryotherapy -- Robotic surgery in prostate cancer -- Radical retropubic prostatectomy in low-high risk prostate cancer -- Guidelines for the delineation of primary tumor target volume in prostate cancer -- Guidelines for the delineation of lymphatic target volumes in prostate cancer -- Modern radiotherapy techniques in prostate cancers -- Protontherapy for prostate cancer -- Brachytherapy for prostate cancer -- Stereotactic body radiotherapy for prostate cancer -- The role of hormonal therapies and radiotherapy in prostate cancer -- The role of hormonal therapies after surgery -- PSA after radiotherapy: Biochemical failure and PSA bounce -- Adjuvant and Salvage Radiotherapy in prostate cancer -- Reirradiation in prostate cancer -- Systemic chemotherapies in the management of prostate cancer -- Translational research and immunotherapy in prostate cancer -- Surgery in superficial and invasive bladder cancer -- Target volume delineation guidelines in bladder cancer -- Bladder preservation therapies in bladder cancer -- Systemic chemotherapies in bladder cancers -- Translational research and immunotherapy in bladder cancer -- Radiolabelled targeted therapies in urological tumors -- Radiation induced toxicity and related management strategies on urological malignancies -- Quality assurance of modern radiotherapy techniques in urological malignancies.
Record Nr. UNINA-9910254489703321
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017
Materiale a stampa
Lo trovi qui: Univ. Federico II
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