AIMC Topic: Image Processing, Computer-Assisted

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Computer Vision-Assisted Data Analysis for Correlative Electron Microscopy and Secondary Ion Mass Spectrometry Imaging.

Analytical chemistry
Correlative imaging is a powerful analytical approach in bioimaging, as it offers complementary information on the samples measured by different modalities. Particularly, correlative transmission electron microscopy (EM) and nanoscale secondary ion m...

Populational influence on cephalometric landmark identification: performance of two AI-driven software programs in Brazilian and Korean images.

BMC oral health
OBJECTIVE: To assess the performance of cephalometric landmark identification performed by two AI-driven software programs in images from different populations (Brazilian and Korean).

A high-resolution temporal transcriptomic and imaging dataset of porcine wound healing.

Scientific data
Wound healing is a dynamic process involving various cell types. Collecting samples from healing wounds and investigating their transcriptomics can provide deeper insights into the underlying processes. In recent years, several experiments have been ...

Transformer-assisted broad learning for hybrid intelligence-based skin cancer segmentation.

Scientific reports
With the rise of Transformer architectures, deep learning applications have gradually shifted from traditional convolutional neural networks to Transformers based on self-attention mechanisms. In tasks such as image classification, segmentation, and ...

Advanced transformer with attention-based neural network framework for precise renal cell carcinoma detection using histological kidney images.

Scientific reports
Renal cell carcinoma (RCC) is one of the typical categories of kidney cancer and is a varied group of malignancies arising from epithelial cells of the kidney parenchyma. RCC has more than ten subtypes. Classification of RCC sub-types is mainly accor...

cryoTIGER: deep-learning based tilt interpolation generator for enhanced reconstruction in cryo electron tomography.

Communications biology
Cryo-electron tomography enables the visualization of macromolecular complexes within native cellular environments but is limited by incomplete angular sampling and the maximal electron dose that biological specimens can be exposed to. Here, we devel...

An intra- and inter-class context and consistency network for supervised and semi-supervised blastocyst segmentation.

Scientific reports
The implantation potential of an embryo is intricately linked to the quality of its blastocyst. Consequently, achieving an objective and precise identification of blastocyst morphology is imperative. The purpose of this study is to focus on the struc...

A deep ensemble learning framework for brain tumor classification using data balancing and fine-tuning.

Scientific reports
Brain tumors are a critical medical challenge, requiring accurate and timely diagnosis to improve patient outcomes. Misclassification can significantly reduce life expectancy, emphasizing the need for precise diagnostic methods. Manual analysis of ex...

Adaptive k-sparse constrained dictionary learning strategy for bioluminescence tomography reconstruction.

Physics in medicine and biology
. Bioluminescence tomography (BLT) is a significant molecular imaging modality with promising potential in biomedical research. However, the reconstruction results of BLT are frequently sensitive and imprecise due to the light scattering effect and i...

Pseudo PET synthesis from CT based on deep neural networks.

Physics in medicine and biology
. Integrated positron emission tomography (PET)/computed tomography (CT) imaging plays a vital role in tumor diagnosis by offering both anatomical and functional information. However, the high cost, limited accessibility of PET imaging and concerns a...