Machine Learning in Medical Imaging : 14th International Workshop, MLMI 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, Proceedings, Part II / edited by Xiaohuan Cao, Xuanang Xu, Islem Rekik, Zhiming Cui, Xi Ouyang.

Format:

Book

Contributor:

Cao, Xiaohuan, editor.

Series:

Lecture Notes in Computer Science, 1611-3349 ; 14349

Language:

English

Subjects (All):

Image processing--Digital techniques.

Image processing.

Computer vision.

Machine learning.

Computer networks.

Social sciences--Data processing.

Social sciences.

Bioinformatics.

Computer Imaging, Vision, Pattern Recognition and Graphics.

Machine Learning.

Computer Communication Networks.

Computer Application in Social and Behavioral Sciences.

Local Subjects:

Computer Imaging, Vision, Pattern Recognition and Graphics.

Machine Learning.

Computer Communication Networks.

Computer Application in Social and Behavioral Sciences.

Bioinformatics.

Physical Description:

1 online resource (501 pages)

Edition:

1st ed. 2024.

Place of Publication:

Cham : Springer Nature Switzerland : Imprint: Springer, 2024.

Summary:

The two-volume set LNCS 14348 and 14139 constitutes the proceedings of the 14th International Workshop on Machine Learning in Medical Imaging, MLMI 2023, held in conjunction with MICCAI 2023, in Vancouver, Canada, in October 2023. The 93 full papers presented in the proceedings were carefully reviewed and selected from 139 submissions. They focus on major trends and challenges in artificial intelligence and machine learning in the medical imaging field, translating medical imaging research into clinical practice. Topics of interests included deep learning, generative adversarial learning, ensemble learning, transfer learning, multi-task learning, manifold learning, reinforcement learning, along with their applications to medical image analysis, computer-aided diagnosis, multi-modality fusion, image reconstruction, image retrieval, cellular image analysis, molecular imaging, digital pathology, etc.

Contents:

GEMTrans: A General, Echocardiography-based, Multi-Level Transformer Framework for Cardiovascular Diagnosis

Unsupervised Anomaly Detection in Medical Images with a Memory-augmented Multi-level Cross-attentional Masked Autoencoder

LMT: Longitudinal Mixing Training a Framework for the Prediction of Disease Progression Using a Single Image

Identifying Alzheimer's Disease-induced Topology Alterations in Structural Networks using Convolutional Neural Networks

Specificity-Aware Federated Graph Learning for Brain Disorder Analysis with Functional MRI

3D Transformer Based on Deformable Patch Location for Differential Diagnosis Between Alzheimer’s Disease and Frontotemporal Dementia

Consisaug: A Consistency-based Augmentation for Polyp Detection in Endoscopy Image Analysis

Cross-view Contrastive Mutual Learning across Masked Autoencoders for Mammography Diagnosis

Modeling Life-span Brain Age from Large-scale Dataset based on Multi-levelInformation Fusion

Boundary-Constrained Graph Network for Tooth Segmentation on 3D Dental Surfaces

FAST-Net: A Coarse-to-fine Pyramid Network for Face-Skull Transformation

Mixing Histopathology Prototypes into Robust Slide-Level Representations for Cancer Subtyping

Consistency Loss for Improved Colonoscopy Landmark Detection with Vision Transformers

Radiomics Boosts Deep Learning Model for IPMN Classification

Class-Balanced Deep Learning with Adaptive Vector Scaling Loss for Dementia Stage Detection

Enhancing Anomaly Detection in Melanoma Diagnosis through Self-Supervised Training and Lesion Comparison

DynBrainGNN: Towards Spatio-Temporal Interpretable Graph Neural Network based on Dynamic Brain Connectome for Psychiatric Diagnosis

Precise localization within the GI tract by combining classification of CNNs and time-series analysis of HMMs

Towards Unified Modality Understanding for Alzheimer's Disease Diagnosis using Incomplete Multi-Modality Data

COVID-19 Diagnosis Based on Swin Transformer Model with Demographic Information Fusion and Enhanced Multi-head Attention Mechanism

MoViT: Memorizing Vision Transformers for Medical Image Analysis

Fact-Checking of AI-Generated Reports

Is Visual Explanation with Grad-CAM More Reliability for Deeper Neural Networks? a Case Study with Automatic Pneumothorax Diagnosis

Group Distributionally Robust Knowledge Distillation

A Bone Lesion Identification Network (BLIN) in Whole Body CT Images

Post-Deployment Adaptation with Access to Source Data via Federated Learning and Source-Target Remote Gradient Alignment

Data-driven Classification of Fatty Liver From 3D Unenhanced Abdominal CT Scans

Replica-based Federated Learning with Heterogeneous Architectures for Graph Super-Resolution

A Multitask Deep Learning Model for Voxel-level Brain Age Estimation

Deep Nearest Neighbors for Anomaly Detectionin Chest X-Rays

CCMix: Curriculum of Class-wise Mixup for Long-tailed Medical Image Classification

MEDKD: Enhancing Medical Image Classification with Multiple Expert Decoupled Knowledge Distillation for Long-Tail Data

Leveraging Ellipsoid Bounding Shapes and Fast R-CNN for Enlarged Perivascular Spaces Detection and Segmentation

Non-Uniform Sampling-Based Breast Cancer Classification

A Scaled Denoising Attention-based Transformer for Breast Cancer Detection and Classification

Distilling Local Texture Features for Colorectal Tissue Classification in Low Data Regimes

Delving into Ipsilateral Mammogram Assessment under Multi-View Network

ARHNet: Adaptive Region Harmonization for Lesion-aware Augmentation to Improve Segmentation Performance

Normative Aging for an Individual’s Full Brain MRI Using Style GANs to Detect Localized Neurodegeneration

Deep Bayesian Quantization for Supervised Neuroimage Search

Triplet Learningfor Chest X-Ray Image Search in Automated COVID-19 Analysis

Cascaded Cross-Attention Networks for Data-Efficient Whole-Slide Image Classification Using Transformers

Enhanced Diagnostic Fidelity in Pathology Whole Slide Image Compression via Deep Learning

RoFormer for Position Aware Multiple Instance Learning in Whole Slide Image Classification

Structural Cycle GAN for Virtual Immunohistochemistry Staining of Gland Markers in the Colon

NCIS: Deep Color Gradient Maps Regression and Three-Class Pixel Classification for Enhanced Neuronal Cell Instance Segmentation in Nissl-Stained Histological Images

Regionalized Infant Brain Cortical Development Based on Multi-view, High-level fMRI Fingerprint.

Notes:

Includes bibliographical references and index.

ISBN:

3-031-45676-9