Pathology

A hierarchical classifier based on human blood plasma fluorescence for non-invasive colorectal cancer screening.

Colorectal cancer (CRC) a leading cause of death by cancer, and screening programs for its early identification are at the heart of the increasing survival rates. To motivate population participation, non-invasive, accurate, scalable and cost-effective diagnosis methods are required. Blood fluorescence spectroscopy provides rich information that can be used for cancer identification. The main chal...

A deep learning framework for supporting the classification of breast lesions in ultrasound images.

In this research, we exploited the deep learning framework to differentiate the distinctive types of lesions and nodules in breast acquired with ultrasound imaging. A biopsy-proven benchmarking dataset was built from 5151 patients cases containing a total of 7408 ultrasound breast images, representative of semi-automatically segmented lesions associated with masses. The dataset comprised 4254 beni...

Automated Analysis of Unregistered Multi-View Mammograms With Deep Learning.

We describe an automated methodology for the analysis of unregistered cranio-caudal (CC) and medio-lateral oblique (MLO) mammography views in order to...

Computer-assisted cytologic diagnosis in pancreatic FNA: An application of neural networks to image analysis.

BACKGROUND: Fine-needle aspiration (FNA) biopsy is an accurate method for the diagnosis of solid pancreatic masses. However, a significant number of c...

Expression of AdipoR1 and AdipoR2 Receptors as Leptin-Breast Cancer Regulation Mechanisms.

The development of breast cancer is influenced by the adipose tissue through the proteins leptin and adiponectin. However, there is little research co...

Multi-label Inductive Matrix Completion for Joint MGMT and IDH1 Status Prediction for Glioma Patients.

MGMT promoter methylation and IDH1 mutation in high-grade gliomas (HGG) have proven to be the two important molecular indicators associated with bette...

Development and evaluation of exemestane-loaded lyotropic liquid crystalline gel formulations.

The use of liquid crystalline (LC) gel formulations for drug delivery has considerably improved the current delivery methods in terms of bioavailabil...

Rapid and accurate intraoperative pathological diagnosis by artificial intelligence with deep learning technology.

Frozen section is widely used for intraoperative pathological diagnosis (IOPD), which is essential for intraoperative decision making. However, frozen...

Breast cancer cell nuclei classification in histopathology images using deep neural networks.

PURPOSE: Cell nuclei classification in breast cancer histopathology images plays an important role in effective diagnose since breast cancer can often...

Identification and segmentation of myelinated nerve fibers in a cross-sectional optical microscopic image using a deep learning model.

BACKGROUND: The morphometric analysis of myelinated nerve fibers of peripheral nerves in cross-sectional optical microscopic images is valuable. Sever...

Detection of lung cancer in exhaled breath with an electronic nose using support vector machine analysis.

Lung cancer is one of the most common malignancies and has a low 5-year survival rate. There are no cheap, simple and widely available screening metho...

Use of Mac-2 binding protein as a biomarker for nonalcoholic fatty liver disease diagnosis.

In contrast to patients with viral hepatitis, patients with nonalcoholic fatty liver disease (NAFLD) can progress to hepatocellular carcinoma during t...

Using Deep Learning for Classification of Lung Nodules on Computed Tomography Images.

Lung cancer is the most common cancer that cannot be ignored and cause death with late health care. Currently, CT can be used to help doctors detect t...

Automated Breast Ultrasound Lesions Detection Using Convolutional Neural Networks.

Breast lesion detection using ultrasound imaging is considered an important step of computer-aided diagnosis systems. Over the past decade, researcher...

Holographic deep learning for rapid optical screening of anthrax spores.

Establishing early warning systems for anthrax attacks is crucial in biodefense. Despite numerous studies for decades, the limited sensitivity of conv...

The Impact of Adding Sentinel Node Biopsy to Extended Pelvic Lymph Node Dissection on Biochemical Recurrence in Prostate Cancer Patients Treated with Robot-Assisted Radical Prostatectomy.

The benefit of adding sentinel node biopsy (SNB) to extended pelvic lymph node dissection (ePLND) remains controversial. The aim of our study was to e...

Microcystin-leucine-arginine Modulates the Expression Patterns of Proinflammatory Cytokines and an Apoptotic Gene in Chicken Liver.

Microcystins (MCs) are included in drinking water and a family of cyclic heptapeptide hepatotoxins that have been implicated in the impairment of live...

A machine learning approach for real-time modelling of tissue deformation in image-guided neurosurgery.

OBJECTIVES: Accurate reconstruction and visualisation of soft tissue deformation in real time is crucial in image-guided surgery, particularly in augm...

A deep convolutional neural network approach to single-particle recognition in cryo-electron microscopy.

BACKGROUND: Single-particle cryo-electron microscopy (cryo-EM) has become a mainstream tool for the structural determination of biological macromolecu...

Machine-learning-based classification of real-time tissue elastography for hepatic fibrosis in patients with chronic hepatitis B.

Hepatic fibrosis is a common middle stage of the pathological processes of chronic liver diseases. Clinical intervention during the early stages of he...