Image thresholding approaches for medical image segmentation-short literature review
Medical image analysis is an invaluable tool in medicine. Different imaging modalities
provide an effective means for mapping images that can feed machine and deep learning …
provide an effective means for mapping images that can feed machine and deep learning …
Nuclei and glands instance segmentation in histology images: a narrative review
Examination of tissue biopsy and quantification of the various characteristics of cellular
processes are clinical benchmarks in cancer diagnosis. Nuclei and glands instance …
processes are clinical benchmarks in cancer diagnosis. Nuclei and glands instance …
Graphical image region extraction with k-means clustering and watershed
With a wide range of applications, image segmentation is a complex and difficult
preprocessing step that plays an important role in automatic visual systems, which accuracy …
preprocessing step that plays an important role in automatic visual systems, which accuracy …
[HTML][HTML] Histopathology-driven prostate cancer identification: A VBIR approach with CLAHE and GLCM insights
Efficient extraction and analysis of histopathological images are crucial for accurate medical
diagnoses, particularly for prostate cancer. This research enhances histopathological image …
diagnoses, particularly for prostate cancer. This research enhances histopathological image …
A hierarchical conditional random field-based attention mechanism approach for gastric histopathology image classification
Abstract In the Gastric Histopathology Image Classification (GHIC) tasks, which are usually
weakly supervised learning missions, there is inevitably redundant information in the …
weakly supervised learning missions, there is inevitably redundant information in the …
Evolutionary deep feature selection for compact representation of gigapixel images in digital pathology
Despite the recent progress in Deep Neural Networks (DNNs) to characterize histopathology
images, compactly representing a gigapixel whole-slide image (WSI) via salient features to …
images, compactly representing a gigapixel whole-slide image (WSI) via salient features to …
Chaotic fitness-dependent quasi-reflected Aquila optimizer for superpixel based white blood cell segmentation
The crisp partitional clustering techniques like K-Means (KM) are an efficient image
segmentation algorithm. However, the foremost concern with crisp partitional clustering …
segmentation algorithm. However, the foremost concern with crisp partitional clustering …
SCGJO: A hybrid golden jackal optimization with a sine cosine algorithm for tackling multilevel thresholding image segmentation
J Zhang, G Zhang, M Kong, T Zhang - Multimedia Tools and Applications, 2024 - Springer
Multilevel thresholding is a fundamental, substantial and constructive technique that has
been widely recognized and concerned in recent years. However, the computational …
been widely recognized and concerned in recent years. However, the computational …
Residual block convolutional auto encoder in content-based medical image retrieval
Approximately 12 percent of men will suffer from prostate cancer during their lifetime. While
some types of this cancer grow slowly and need minimal treatment, others are aggressive …
some types of this cancer grow slowly and need minimal treatment, others are aggressive …
基于无监督学习的低照度图像增强算法
苏赋， 敬梁， 罗仁泽， 王龙业， 张凯信… - … of Optoelectronics· Laser, 2023 - opticsjournal.net
摘要针对目前低照度图像增强算法存在恢复细节丢失, 网络复杂度高和配对数据集获取难度大等
问题, 提出了一种基于无监督学习的图像增强算法. 在YIQ 色彩空间中, 通过构建的轻量化网络和 …
问题, 提出了一种基于无监督学习的图像增强算法. 在YIQ 色彩空间中, 通过构建的轻量化网络和 …