Artificial Intelligence in Radiation Therapy

First International Workshop, AIRT 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Proceedings

AvDan Nguyen,Lei Xing

Häftad, Engelska, 2019

Del 11850 i serien Lecture Notes in Computer Science

544 kr

Beställningsvara. Skickas inom 10-15 vardagar. Fri frakt över 249 kr.

Beskrivning

This book constitutes the refereed proceedings of the First International Workshop on Connectomics in Artificial Intelligence in Radiation Therapy, AIRT 2019, held in conjunction with MICCAI 2019 in Shenzhen, China, in October 2019.The 20 full papers presented were carefully reviewed and selected from 24 submissions. The papers discuss the state of radiation therapy, the state of AI and related technologies, and hope to find a pathway to revolutionizing the field to ultimately improve cancer patient outcome and quality of life.

Produktinformation

Utgivningsdatum:2019-10-18
Mått:155 x 235 x 11 mm
Vikt:289 g
Format:Häftad
Språk:Engelska
Serie:Lecture Notes in Computer Science
Antal sidor:172
Förlag:Springer Nature Switzerland AG
ISBN:9783030324858

Utforska kategorier

Systemvetenskap och AI inom Data och IT
Artificiell intelligens inom Data och IT
Tillämpad datateknik inom Data och IT

Innehållsförteckning

Using Supervised Learning and Guided Monte Carlo Tree Search for Beam Orientation Optimization in Radiation Therapy.- Feasibility of CT-only 3D dose prediction for VMAT prostate plans using deep learning.- Automatically Tracking and Detecting Signiﬁcant Nodal Mass Shrinkage During Head-and-Neck Radiation Treatment Using Image Saliency.- 4D-CT Deformable Image Registration Using an Unsupervised Deep Convolutional Neural Network.- Toward markerless image-guided radiotherapy using deep learning for prostate cancer.- A Two-Stage Approach for Automated Prostate Lesion Detection and Classification with Mask R-CNN and Weakly Supervised Deep Neural Network.- A Novel Deep Learning Framework for Standardizing the Label of OARs in CT.- Multimodal Volume-Aware Detection and Segmentation for Brain Metastases Radiosurgery.- Voxel-level Radiotherapy Dose Prediction Using Densely Connected Network with Dilated Convolutions.- Online Target Volume Estimation and Prediction From an Interlaced Slice Acquisition - A Manifold Embedding and Learning Approach.- One-dimensional convolutional network for Dosimetry Evaluation at Organs-at-Risk in Esophageal Radiation Treatment Planning.- Unpaired Synthetic Image Generation in Radiology Using GANs.- Deriving lung perfusion directly from CT image using deep convolutional neural network: A preliminary study.- Individualized 3D Dose Distribution Prediction Using Deep Learning.- Deep Generative Model-Driven Multimodal Prostate Segmentation in Radiotherapy.- Dose Distribution Prediction for Optimal Treatment of Modern External Beam Radiation Therapy for Nasopharyngeal Carcinoma.- DeepMCDose: A Deep Learning Method for Efficient Monte Carlo Beamlet Dose Calculation by Predictive Denoising in MR-Guided Radiotherapy.- UC-GAN for MR to CT Image Synthesis.- CBCT-based Synthetic MRI Generation for CBCT-guided Adaptive Radiotherapy.- Cardio-pulmonary Substructure Segmentation of CT images using Convolutional Neural Networks.

Du kanske också är intresserad av

Artificial Intelligence in Radiation Therapy

Steve Jiang, Lei Xing, Dan Nguyen

E-bok

2019

710 kr

Domain Adaptation and Representation Transfer and Medical Image Learning with Less Labels and Imperfect Data

Ngan Le, Khoa Luu, Kevin Zhou, Steve Jiang, Badri Roysam, Vishal Patel, Konstantinos Kamnitsas, Ziyue Xu, Nicola Rieke, M. Jorge Cardoso, Shadi Albarqouni, Hien V. Nguyen, Fausto Milletari, Qian Wang

E-bok

2019

710 kr

Qian Wang, Fausto Milletari, Hien V. Nguyen, Shadi Albarqouni, M. Jorge Cardoso, Nicola Rieke, Ziyue Xu, Konstantinos Kamnitsas, Vishal Patel, Badri Roysam, Steve Jiang, Kevin Zhou, Khoa Luu, Ngan Le - Domain Adaptation and Representation Transfer and Medical Image Learning with Less Labels and Imperfect Data, Häftad

Del 11795

Domain Adaptation and Representation Transfer and Medical Image Learning with Less Labels and Imperfect Data

Qian Wang, Fausto Milletari, Hien V. Nguyen, Shadi Albarqouni, M. Jorge Cardoso, Nicola Rieke, Ziyue Xu, Konstantinos Kamnitsas, Vishal Patel, Badri Roysam, Steve Jiang, Kevin Zhou, Khoa Luu, Ngan Le

Häftad, 2019

544 kr

Jaime Cardoso, Hien Van Nguyen, Nicholas Heller, Pedro Henriques Abreu, Ivana Isgum, Wilson Silva, Ricardo Cruz, Jose Pereira Amorim, Vishal Patel, Badri Roysam, Kevin Zhou, Steve Jiang, Ngan Le, Khoa Luu, Raphael Sznitman, Veronika Cheplygina, Diana Mateus, Emanuele Trucco, Samaneh Abbasi - Interpretable and Annotation-Efficient Learning for Medical Image Computing, Häftad

Del 12446

Interpretable and Annotation-Efficient Learning for Medical Image Computing

Jaime Cardoso, Hien Van Nguyen, Nicholas Heller, Pedro Henriques Abreu, Ivana Isgum, Wilson Silva, Ricardo Cruz, Jose Pereira Amorim, Vishal Patel, Badri Roysam, Kevin Zhou, Steve Jiang, Ngan Le, Khoa Luu, Raphael Sznitman, Veronika Cheplygina, Diana Mateus, Emanuele Trucco, Samaneh Abbasi

Häftad, 2020

544 kr

Interpretable and Annotation-Efficient Learning for Medical Image Computing

Samaneh Abbasi, Emanuele Trucco, Diana Mateus, Veronika Cheplygina, Raphael Sznitman, Khoa Luu, Ngan Le, Steve Jiang, Kevin Zhou, Badri Roysam, Vishal Patel, Jose Pereira Amorim, Ricardo Cruz, Wilson Silva, Ivana Isgum, Pedro Henriques Abreu, Nicholas Heller, Hien Van Nguyen, Jaime Cardoso