Pathology

Intra- and Interspecies Variability of Single-Cell Innate Fluorescence Signature of Microbial Cell.

Here we analyzed the innate fluorescence signature of the single microbial cell, within both clonal and mixed populations of microorganisms. We found that even very similarly shaped cells differ noticeably in their autofluorescence features and that the innate fluorescence signatures change dynamically with growth phases. We demonstrated that machine learning models can be trained with a data set ...

Prediction of Immunohistochemistry of Suspected Thyroid Nodules by Use of Machine Learning-Based Radiomics.

The purpose of this study was to develop and validate a radiomics model for evaluating immunohistochemical characteristics in patients with suspected thyroid nodules. A total of 103 patients (training cohort-to-validation cohort ratio, ≈ 3:1) with suspected thyroid nodules who had undergone thyroidectomy and immunohistochemical analysis were enrolled. The immunohistochemical markers were cytoker...

An Effective CNN Method for Fully Automated Segmenting Subcutaneous and Visceral Adipose Tissue on CT Scans.

One major role of an accurate distribution of abdominal adipose tissue is to predict disease risk. This paper proposes a novel effective three-level c...

Design and control of a MRI-compatible pneumatic needle puncture robot.

Percutaneous needle puncture operation is widely used in the image-guided interventions, including biopsy and ablation. MRI guidance has the advantage...

Caveolae and scaffold detection from single molecule localization microscopy data using deep learning.

Caveolae are plasma membrane invaginations whose formation requires caveolin-1 (Cav1), the adaptor protein polymerase I, and the transcript release fa...

A 3D Spatially Weighted Network for Segmentation of Brain Tissue From MRI.

The segmentation of brain tissue in MRI is valuable for extracting brain structure to aid diagnosis, treatment and tracking the progression of differe...

Automated classification of gastric neoplasms in endoscopic images using a convolutional neural network.

BACKGROUND: Visual inspection, lesion detection, and differentiation between malignant and benign features are key aspects of an endoscopist's role. T...

Quantifying the effects of data augmentation and stain color normalization in convolutional neural networks for computational pathology.

Stain variation is a phenomenon observed when distinct pathology laboratories stain tissue slides that exhibit similar but not identical color appeara...

Learning to detect lymphocytes in immunohistochemistry with deep learning.

The immune system is of critical importance in the development of cancer. The evasion of destruction by the immune system is one of the emerging hallm...

From Discrete to Continuous Modeling of Lymphocyte Development and Plasticity in Chronic Diseases.

The molecular events leading to differentiation, development, and plasticity of lymphoid cells have been subject of intense research due to their key ...

Classification of Volumetric Images Using Multi-Instance Learning and Extreme Value Theorem.

Volumetric imaging is an essential diagnostic tool for medical practitioners. The use of popular techniques such as convolutional neural networks (CNN...

Flow regime identification for air valves failure evaluation in water pipelines using pressure data.

Air valve failure can cause air accumulation and result in a loss of carrying capacity, pipe vibration and even in some situations a catastrophic fail...

Increase Trichomonas vaginalis detection based on urine routine analysis through a machine learning approach.

Trichomonas vaginalis (T. vaginalis) detection remains an unsolved problem in using of automated instruments for urinalysis. The study proposes a mach...

mDixon-Based Synthetic CT Generation for PET Attenuation Correction on Abdomen and Pelvis Jointly Using Transfer Fuzzy Clustering and Active Learning-Based Classification.

We propose a new method for generating synthetic CT images from modified Dixon (mDixon) MR data. The synthetic CT is used for attenuation correction (...

Performance of an artificial intelligence algorithm for reporting urine cytopathology.

BACKGROUND: Unlike Papanicolaou tests, there are no commercially available computer-assisted automated screening systems for urine specimens. Despite ...

Unsupervised method for normalization of hematoxylin-eosin stain in histological images.

Histological images stained with hematoxylin-eosin are widely used by pathologists for cancer diagnosis. However, these images can have color variatio...

Multi-Task Deep Model With Margin Ranking Loss for Lung Nodule Analysis.

Lung cancer is the leading cause of cancer deaths worldwide and early diagnosis of lung nodule is of great importance for therapeutic treatment and sa...

Classification and Segmentation of Hyperspectral Data of Hepatocellular Carcinoma Samples Using 1-D Convolutional Neural Network.

Pathological diagnosis plays an important role in the diagnosis and treatment of hepatocellular carcinoma (HCC). The traditional method of pathologica...

An augmented reality microscope with real-time artificial intelligence integration for cancer diagnosis.

The microscopic assessment of tissue samples is instrumental for the diagnosis and staging of cancer, and thus guides therapy. However, these assessme...

An investigation of CNN models for differentiating malignant from benign lesions using small pathologically proven datasets.

Cancer has been one of the most threatening diseases to human health. There have been many efforts devoted to the advancement of radiology and transfo...