2022 IEEE International Symposium on Biomedical Imaging Challenges (ISBIC) / IEEE.

Format:

Book

Author/Creator:

Institute of Electrical and Electronics Engineers, author, issuing body.

Language:

English

Subjects (All):

Diagnostic imaging--Congresses.

Diagnostic imaging.

Physical Description:

1 online resource : illustrations

Other Title:

2022 IEEE International Symposium on Biomedical Imaging Challenges

Place of Publication:

Piscataway, NJ : IEEE, 2022.

Summary:

The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging ISBI 2022 will be the 19th meeting in this series The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging The 2022 meeting will continue this tradition of fostering cross fertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.

Contents:

A Multi-Task Multiple Instance Learning Algorithm to Analyze Large Whole Slide Images from Bright Challenge 2022,"N.

Breast Tumor Image Classification in Bright Challenge VIA Multiple Instance Learning and Deep Transformers,"Y.

Class-Controlling Copy-Paste Augmentation for Nuclear Segmentation,"H.

Panoptic segmentation with highly imbalanced semantic labels,"J.

Deep Dirichlet Uncertainty for Unsupervised Out-of-Distribution Detection of Eye Fundus Photographs in Glaucoma Screening,"T.

Elevating Fundoscopic Evaluation to Expert Level - Automatic Glaucoma Detection Using Data from the Airogs Challenge,"F.

Multi-Modal Information Fusion for Classification of Kidney Abnormalities,"V.

Risk Score Classification of Renal Masses on CT Imaging Data Using a Convolutional Neural Network,"D.

Deep Learning-Based Methods for Directing the Management of Renal Cancer Using CT Scan and Clinical Information,"S.

Ciscnet - a Single-Branch Cell Nucleus Instance Segmentation and Classification Network,"M.

Nuclei Instance Segmentation and Classification in Histopathology Images with Stardist,"M.

Multiple-Instance Learning with Efficient Transformer for Breast Tumor Image Classification in Bright Challenge,"F.

Color Space-based HoVer-Net for Nuclei Instance Segmentation and Classification,"H.

A Workflow for Computer-Aided Diagnosis of Glaucoma,"H.

Notes:

Description based on publisher supplied metadata and other sources.

ISBN:

1-66545-172-6