Medical Image Learning with Limited and Noisy Data

Second International Workshop, MILLanD 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, Proceedings

AvZhiyun Xue,Sameer Antani

Häftad, Engelska, 2023

Del 14307 i serien Lecture Notes in Computer Science

1 317 kr

Beställningsvara. Skickas inom 5-8 vardagar. Fri frakt över 249 kr.

Beskrivning

This book consists of full papers presented in the 2nd workshop of ”Medical Image Learning with Noisy and Limited Data (MILLanD)” held in conjunction with the 26th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2023).The 24 full papers presented were carefully reviewed and selected from 38 submissions. The conference focused on challenges and limitations of current deep learning methods applied to limited and noisy medical data and present new methods for training models using such imperfect data.

Produktinformation

Utgivningsdatum:2023-10-31
Mått:155 x 235 x 16 mm
Vikt:435 g
Format:Häftad
Språk:Engelska
Serie:Lecture Notes in Computer Science
Antal sidor:270
Upplaga:23001
Förlag:Springer International Publishing AG
ISBN:9783031471964

Utforska kategorier

Systemvetenskap och AI inom Data och IT

Innehållsförteckning

Efficient Annotation and Training Strategies.- Reducing Manual Annotation Costs for Cell Segmentation by Upgrading Low-quality Annotations.- ScribSD: Scribble-supervised Fetal MRI Segmentation based on Simultaneous Feature and Prediction Self-Distillation.- Label-efficient Contrastive Learning-based Model for Nuclei Detection and Classification in 3D Cardiovascular Immunofluorescent Images.- Affordable Graph Neural Network Framework using Topological Graph Contraction.- Approaches for Noisy, Missing, and Low Quality Data.- Dual-domain Iterative Network with Adaptive Data Consistency for Joint Denoising and Few-angle Reconstruction of Low-dose Cardiac SPECT.- A Multitask Framework for Label Refinement and Lesion Segmentation in Clinical Brain Imaging.- COVID-19 Lesion Segmentation Framework for the Contrast-enhanced CT in the Absence of Contrast-enhanced CT Annotation.- Feasibility of Universal Anomaly Detection without Knowingthe Abnormality in Medical Image.- Unsupervised, Self-supervised, and Contrastive Learning.- Decoupled Conditional Contrastive Learning with Variable Metadata for Prostate Lesion Detection.- FBA-Net: Foreground and Background Aware Contrastive Learning for Semi-Supervised Atrium Segmentation.- Masked Image Modeling for Label-Efficient Segmentation in Two-Photon Excitation Microscopy.- Automatic Quantification of COVID-19 Pulmonary Edema by Self-supervised Contrastive Learning.- SDLFormer: A Sparse and Dense Locality-enhanced Transformer for Accelerated MR Image Reconstruction.- Robust Unsupervised Image to Template Registration Without Image Similarity Los.- A Dual-Branch Network with Mixed and Self-Supervision for Medical Image Segmentation: An Application to Segment Edematous Adipose Tissue.- Weakly-supervised, Semi-supervised, and Multitask Learning.- Combining Weakly Supervised Segmentation with Multitask Learning forImproved 3D MRI Brain Tumour Classification.- Exigent Examiner and Mean Teacher: An Advanced 3D CNN-based Semi-Supervised Brain Tumor Segmentation Framework.- Extremely Weakly-supervised Blood Vessel Segmentation with Physiologically Based Synthesis and Domain Adaptation.- Multi-Task Learning for Few-Shot Differential Diagnosis of Breast Cancer Histopathology Image.- Active Learning.- Efficient Annotation for Medical Image Analysis: A One-Pass Selective Annotation Approach.- Test-time Augmentation-based Active Learning and Self-training for Label-efficient Segmentation.- Active Transfer Learning for 3D Hippocampus Segmentation.- Transfer Learning.- Using Training Samples as Transitive Information Bridges in Predicted 4D MRI.- To Pretrain or not to Pretrain? A Case Study of Domain-Specific Pretraining for Semantic Segmentation in Histopathology.- Large-scale Pretraining on Pathological Images for Fine-tuning of Small Pathological Benchmarks.

Du kanske också är intresserad av

Del 13559

Medical Image Learning with Limited and Noisy Data

Ghada Zamzmi, Sameer Antani, Ulas Bagci, Marius George Linguraru, Sivaramakrishnan Rajaraman, Zhiyun Xue

Häftad

556 kr

Del 14307

Philosophie-Kurs mit Seneca

Peter Günzel

Häftad

99 kr

Del 13003

Deep Generative Models, and Data Augmentation, Labelling, and Imperfections

Sandy Engelhardt, Ilkay Oksuz, Dajiang Zhu, Yixuan Yuan, Anirban Mukhopadhyay, Nicholas Heller, Sharon Xiaolei Huang, Hien Nguyen, Raphael Sznitman, Yuan Xue

Häftad

689 kr

AI-Driven Breakthroughs in Antimicrobial Resistance

Hemachandran Kannan, Raul Villamarin Rodriguez, Sivaramakrishnan Rajaraman, Anil Audumbar Pise

Inbunden

5 681 kr

Del 12929

Interpretability of Machine Intelligence in Medical Image Computing, and Topological Data Analysis and Its Applications for Medical Data

Mauricio Reyes, Pedro Henriques Abreu, Jaime Cardoso, Mustafa Hajij, Ghada Zamzmi, Paul Rahul, Lokendra Thakur

Häftad

593 kr

Necrobotics for Healthcare Applications and Management

Kannan,Hemachandra, Hemachandran Kannan, Murugappan Murugappan, Raul Villamarin Rodriguez, Sivaramakrishnan Rajaraman, Rajesh Kumar K V

Häftad

1 765 kr

Del 15198

Ethics and Fairness in Medical Imaging

Esther Puyol-Antón, Ghada Zamzmi, Aasa Feragen, Andrew P. King, Veronika Cheplygina, Melanie Ganz-Benjaminsen, Enzo Ferrante, Ben Glocker, Eike Petersen, John S. H. Baxter, Islem Rekik, Roy Eagleson

Häftad

608 kr

Del 16135

Bridging Regulatory Science and Medical Imaging Evaluation; and Distributed, Collaborative, and Federated Learning

Ghada Zamzmi, Annika Reinke, Ravi Samala, Meirui Jiang, Xiaoxiao Li, Holger Roth, Mariia Sidulova, Thijs Kooi, Shadi Albarqouni, Spyridon Bakas, Nicola Rieke

Häftad

640 kr

Del 14393

Medical Image Computing and Computer Assisted Intervention – MICCAI 2023 Workshops

M. Emre Celebi, Md Sirajus Salekin, Hyunwoo Kim, Shadi Albarqouni, Catarina Barata, Allan Halpern, Philipp Tschandl, Marc Combalia, Yuan Liu, Ghada Zamzmi, Joshua Levy, Huzefa Rangwala, Annika Reinke, Diya Wynn, Bennett Landman, Won-Ki Jeong, Yiqing Shen, Zhongying Deng, Spyridon Bakas, Xiaoxiao Li, Chen Qin, Nicola Rieke, Holger Roth, Daguang Xu

Häftad

826 kr

Del 14277

Predictive Intelligence in Medicine

Islem Rekik, Ehsan Adeli, Sang Hyun Park, Celia Cintas, Ghada Zamzmi

Häftad

1 214 kr

Företag, bibliotek eller offentlig verksamhet?

Medical Image Learning with Limited and Noisy Data

Second International Workshop, MILLanD 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, Proceedings

Beskrivning

Produktinformation

Utforska kategorier

Innehållsförteckning

Du kanske också är intresserad av

Medical Image Learning with Limited and Noisy Data

Philosophie-Kurs mit Seneca

Deep Generative Models, and Data Augmentation, Labelling, and Imperfections

AI-Driven Breakthroughs in Antimicrobial Resistance

Interpretability of Machine Intelligence in Medical Image Computing, and Topological Data Analysis and Its Applications for Medical Data

Necrobotics for Healthcare Applications and Management

Ethics and Fairness in Medical Imaging

Bridging Regulatory Science and Medical Imaging Evaluation; and Distributed, Collaborative, and Federated Learning

Medical Image Computing and Computer Assisted Intervention – MICCAI 2023 Workshops

Predictive Intelligence in Medicine

Mina sidor

Mina sidor

Hjälp

Hjälp

Om Bokus

Om Bokus

Populärt

Populärt

Inspiration

Inspiration