Xuming zhang (31 resultados)

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Paperback or Softback. Condición: New. Advances in Optofluidics. Book.

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Paperback. Condición: New.

Paperback. Condición: New.

Condición: New. In English.

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HRD. Condición: New. New Book. Shipped from UK. Established seller since 2000.

HRD. Condición: New. New Book. Shipped from UK. Established seller since 2000.

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Taschenbuch. Condición: Neu. Neuware - Optofluidics a niche research field that integrates optics with microfluidics. It started with elegant demonstrations of the passive interaction of light and liquid media such as liquid waveguides and liquid tunable lenses. Recently, the optofluidics continues the advance in liquid-based optical devices/systems. In addition, it has expanded rapidly into many other fields that involve lightwave (or photon) and liquid media. This Special Issue invites review articles (only review articles) that update the latest progress of the optofluidics in various aspects, such as new functional devices, new integrated systems, new fabrication techniques, new applications, etc. It covers, but is not limited to, topics such as micro-optics in liquid media, optofluidic sensors, integrated micro-optical systems, displays, optofluidics-on-fibers, optofluidic manipulation, energy and environmental applciations, and so on.…

Paperback. Condición: New.

Condición: New. KlappentextrnrnOptofluidics a niche research field that integrates optics with microfluidics. It started with elegant demonstrations of the passive interaction of light and liquid media such as liquid waveguides and liquid tunable lenses. Recent.

Paperback. Condición: New.

Condición: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.

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Condición: As New. Unread book in perfect condition.

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PAP. Condición: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Condición: New. Print on Demand pp. 148.

Condición: New. Print on Demand pp. 148.

Condición: New. PRINT ON DEMAND pp. 148.

Hardcover. Condición: new. Hardcover. Multi-sensor fusion plays an important role in medical imaging, diagnosis and therapy. Recently, with the advancement of various imaging modalities such as ultrasound, computer tomography (CT), magnetic resonance imaging (MRI) and positron emission tomography (PET), the fusion of various imaging data has aroused great interest among researchers. Effective fusion algorithms significantly influence the quality of fused data, thereby affecting final diagnoses and chosen therapies. Traditional fusion methods based on sparse representation and multi-scale decomposition have been explored in depth. Deep learning-based fusion methods can generally deliver efficient data fusion by combining the convolutional neural network or transformer and unsupervised loss function. As part of the research on fusion methods, great efforts have been made to explore the application of fusion methods in disease diagnosis and therapy, such as PET-CT fusion for lung cancer detection and MR-ultrasound fusion for targeted prostate biopsy. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Hardcover. Condición: new. Hardcover. Multi-sensor fusion plays an important role in medical imaging, diagnosis and therapy. Recently, with the advancement of various imaging modalities such as ultrasound, computer tomography (CT), magnetic resonance imaging (MRI) and positron emission tomography (PET), the fusion of various imaging data has aroused great interest among researchers. Effective fusion algorithms significantly influence the quality of fused data, thereby affecting final diagnoses and chosen therapies. Traditional fusion methods based on sparse representation and multi-scale decomposition have been explored in depth. Deep learning-based fusion methods can generally deliver efficient data fusion by combining the convolutional neural network or transformer and unsupervised loss function. As part of the research on fusion methods, great efforts have been made to explore the application of fusion methods in disease diagnosis and therapy, such as PET-CT fusion for lung cancer detection and MR-ultrasound fusion for targeted prostate biopsy. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Hardcover. Condición: new. Hardcover. Multi-sensor fusion plays an important role in medical imaging, diagnosis and therapy. Recently, with the advancement of various imaging modalities such as ultrasound, computer tomography (CT), magnetic resonance imaging (MRI) and positron emission tomography (PET), the fusion of various imaging data has aroused great interest among researchers. Effective fusion algorithms significantly influence the quality of fused data, thereby affecting final diagnoses and chosen therapies. Traditional fusion methods based on sparse representation and multi-scale decomposition have been explored in depth. Deep learning-based fusion methods can generally deliver efficient data fusion by combining the convolutional neural network or transformer and unsupervised loss function. As part of the research on fusion methods, great efforts have been made to explore the application of fusion methods in disease diagnosis and therapy, such as PET-CT fusion for lung cancer detection and MR-ultrasound fusion for targeted prostate biopsy. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…

Buch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Multi-sensor fusion plays an important role in medical imaging, diagnosis and therapy. Recently, with the advancement of various imaging modalities such as ultrasound, computer tomography (CT), magnetic resonance imaging (MRI) and positron emission tomography (PET), the fusion of various imaging data has aroused great interest among researchers. Effective fusion algorithms significantly influence the quality of fused data, thereby affecting final diagnoses and chosen therapies. Traditional fusion methods based on sparse representation and multi-scale decomposition have been explored in depth. Deep learning-based fusion methods can generally deliver efficient data fusion by combining the convolutional neural network or transformer and unsupervised loss function. As part of the research on fusion methods, great efforts have been made to explore the application of fusion methods in disease diagnosis and therapy, such as PET-CT fusion for lung cancer detection and MR-ultrasound fusion for targeted prostate biopsy.…