Entropy Based Medical Image Segmentation

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Loss odyssey in medical image segmentation

https://www.sciencedirect.com/science/article/pii/S1361841521000815

Recently, cross entropy and Dice loss have become the most commonly used loss functions in medical image segmentation tasks ( Milletari et al., 2016 ). For example, in the proceedings of MICCAI 2018, 47 out of 77 CNN-based segmentation papers ( …

Unified Focal loss: Generalising Dice and cross entropy …

https://pubmed.ncbi.nlm.nih.gov/34953431/

Unified Focal loss: Generalising Dice and cross entropy-based losses to handle class imbalanced medical image segmentation Automatic segmentation methods are an …

O2M-UDA: Unsupervised dynamic domain adaptation for …

https://www.sciencedirect.com/science/article/abs/pii/S0950705123001284

One-to-multiple medical image segmentation aims to directly test a segmentation model trained with the medical images of a one-domain site on those of a …

Local and Global Structure-Aware Entropy Regularized …

https://link.springer.com/chapter/10.1007/978-3-030-59710-8_55

Abstract. Emerging self-ensembling methods have achieved promising semi-supervised segmentation performances on medical images through forcing …

A Review of Deep-Learning-Based Medical Image …

https://www.mdpi.com/2071-1050/13/3/1224

Image segmentation based on medical imaging is the use of computer image processing technology to analyze and process 2D …

Entropy-Based Automatic Segmentation of Bones in …

https://www.researchgate.net/profile/Oishila-Bandyopadhyay/publication/221205076_Entropy-Based_Automatic_Segmentation_of_Bones_in_Digital_X-ray_Images/links/561f711a08aecade1ace35f9/Entropy-Based-Automatic-Segmentation-of-Bones-in-Digital-X-ray-Images.pdf

Medical image segmentation algorithms can be classified into categories like those based on analysis of edges, regions, pixel classification, graphs, or on deformable model, fuzzy …

Novel medical image cryptogram technology based on …

https://link.springer.com/article/10.1007/s11042-023-14546-3

Medical images (MRI, CT, X-rays) with large data storage, redundancy, and high pixel correlation are easily tampered with or attacked. Besides, with the rapid growth …

Generalized α-Entropy Based Medical Image Segmentation

https://www.scirp.org/journal/PaperInformation.aspx?PaperID=42203

In this paper, an efficient and fast entropic method for noisy cell image segmentation is presented. The method utilizes generalized α-entropy to measure the maximum …

[0911.1759] An entropy-based approach to automatic image …

https://ar5iv.labs.arxiv.org/html/0911.1759

An entropy-based image segmentation approach is introduced and applied to color images obtained from Google Earth. Segmentation refers to the process of …

Explainable multi-module semantic guided attention …

https://dlnext.acm.org/doi/10.1016/j.compbiomed.2022.106231

Medical image segmentation has been improved based on the convolutional neural networks (C... Highlights • Propose an multi-module attention based network (MSGA …

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