Pathology

Artificial intelligence identifies inflammation and confirms fibroblast foci as prognostic tissue biomarkers in idiopathic pulmonary fibrosis.

A large number of fibroblast foci (FF) predict mortality in idiopathic pulmonary fibrosis (IPF). Other prognostic histological markers have not been identified. Artificial intelligence (AI) offers a possibility to quantitate possible prognostic histological features in IPF. We aimed to test the use of AI in IPF lung tissue samples by quantitating FF, interstitial mononuclear inflammation, and intr...

Deep learning networks on chronic liver disease assessment with fine-tuning of shear wave elastography image sequences.

Chronic liver disease (CLD) is currently one of the major causes of death worldwide. If not treated, it may lead to cirrhosis, hepatic carcinoma and death. Ultrasound (US) shear wave elastography (SWE) is a relatively new, popular, non-invasive technique among radiologists. Although many studies have been published validating the SWE technique either in a clinical setting, or by applying machine l...

NucleiSegNet: Robust deep learning architecture for the nuclei segmentation of liver cancer histopathology images.

The nuclei segmentation of hematoxylin and eosin (H&E) stained histopathology images is an important prerequisite in designing a computer-aided diagno...

Challenges Developing Deep Learning Algorithms in Cytology.

BACKGROUND: The incorporation of digital pathology into routine pathology practice is becoming more widespread. Definite advantages exist with respect...

Review of Laser Raman Spectroscopy for Surgical Breast Cancer Detection: Stochastic Backpropagation Neural Networks.

Laser Raman spectroscopy (LRS) is a highly specific biomolecular technique which has been shown to have the ability to distinguish malignant and norma...

Evaluation of the Use of Combined Artificial Intelligence and Pathologist Assessment to Review and Grade Prostate Biopsies.

IMPORTANCE: Expert-level artificial intelligence (AI) algorithms for prostate biopsy grading have recently been developed. However, the potential impa...

A novel extended Kalman filter with support vector machine based method for the automatic diagnosis and segmentation of brain tumors.

BACKGROUND: Brain tumors are life-threatening, and their early detection is crucial for improving survival rates. Conventionally, brain tumors are det...

Roto-translation equivariant convolutional networks: Application to histopathology image analysis.

Rotation-invariance is a desired property of machine-learning models for medical image analysis and in particular for computational pathology applicat...

Detecting Vasodilation as Potential Diagnostic Biomarker in Breast Cancer Using Deep Learning-Driven Thermomics.

Breast cancer is the most common cancer in women. Early diagnosis improves outcome and survival, which is the cornerstone of breast cancer treatment. ...

Intraprostatic Tumor Segmentation on PSMA PET Images in Patients with Primary Prostate Cancer with a Convolutional Neural Network.

Accurate delineation of the intraprostatic gross tumor volume (GTV) is a prerequisite for treatment approaches in patients with primary prostate cance...

Deep Adversarial Training for Multi-Organ Nuclei Segmentation in Histopathology Images.

Nuclei mymargin segmentation is a fundamental task for various computational pathology applications including nuclei morphology analysis, cell type cl...

Deep Learning-Based Spectral Unmixing for Optoacoustic Imaging of Tissue Oxygen Saturation.

Label free imaging of oxygenation distribution in tissues is highly desired in numerous biomedical applications, but is still elusive, in particular i...

Weakly Supervised Deep Nuclei Segmentation Using Partial Points Annotation in Histopathology Images.

Nuclei segmentation is a fundamental task in histopathology image analysis. Typically, such segmentation tasks require significant effort to manually ...

Artificial intelligence-based image classification methods for diagnosis of skin cancer: Challenges and opportunities.

Recently, there has been great interest in developing Artificial Intelligence (AI) enabled computer-aided diagnostics solutions for the diagnosis of s...

A large-scale optical microscopy image dataset of potato tuber for deep learning based plant cell assessment.

We present a new large-scale three-fold annotated microscopy image dataset, aiming to advance the plant cell biology research by exploring different c...

Thyroid Nodule Classification for Physician Decision Support Using Machine Learning-Evaluated Geometric and Morphological Features.

The classification of thyroid nodules using ultrasound (US) imaging is done using the Thyroid Imaging Reporting and Data System (TIRADS) guidelines th...

Identifying gross post-mortem organ images using a pre-trained convolutional neural network.

Identifying organs/tissue and pathology on radiological and microscopic images can be performed using convolutional neural networks (CNN). However, th...

Super-Resolved q-Space deep learning with uncertainty quantification.

Diffusion magnetic resonance imaging (dMRI) provides a noninvasive method for measuring brain tissue microstructure. q-Space deep learning(q-DL) metho...

Realizing 5G- and AI-based doctor-to-doctor remote diagnosis: opportunities, challenges, and prospects.

Fifth Generation (5G) mobile communications technology became available in Japan as of the end of March 2020. The Ministry of Internal Affairs and Com...

Potential Candidates for Focal Therapy in Prostate Cancer in the Era of Magnetic Resonance Imaging-targeted Biopsy: A Large Multicenter Cohort Study.

BACKGROUND: Focal therapy (FT) with its favorable side-effect profile represents an option between active surveillance and traditional whole-gland tre...