AIMC Topic: Deep Learning

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Automatic Pancreatic Cyst Lesion Segmentation on EUS Images Using a Deep-Learning Approach.

Sensors (Basel, Switzerland)
The automatic segmentation of the pancreatic cyst lesion (PCL) is essential for the automated diagnosis of pancreatic cyst lesions on endoscopic ultrasonography (EUS) images. In this study, we proposed a deep-learning approach for PCL segmentation on...

A highly accurate delta check method using deep learning for detection of sample mix-up in the clinical laboratory.

Clinical chemistry and laboratory medicine
OBJECTIVES: Delta check (DC) is widely used for detecting sample mix-up. Owing to the inadequate error detection and high false-positive rate, the implementation of DC in real-world settings is labor-intensive and rarely capable of absolute detection...

SAFRON: Stitching Across the Frontier Network for Generating Colorectal Cancer Histology Images.

Medical image analysis
Automated synthesis of histology images has several potential applications including the development of data-efficient deep learning algorithms. In the field of computational pathology, where histology images are large in size and visual context is c...

Multi-energy level fusion for nodal metastasis classification of primary lung tumor on dual energy CT using deep learning.

Computers in biology and medicine
Lymph node metastasis also called nodal metastasis (Nmet), is a clinically primary task for physicians. The survival and recurrence of lung cancer are related to the Nmet staging from Tumor-Node-Metastasis (TNM) reports. Furthermore, preoperative Nme...

Fully automatic pipeline of convolutional neural networks and capsule networks to distinguish COVID-19 from community-acquired pneumonia via CT images.

Computers in biology and medicine
BACKGROUND: Chest computed tomography (CT) is crucial in the diagnosis of coronavirus disease 2019 (COVID-19). However, the persistent pandemic and similar CT manifestations between COVID-19 and community-acquired pneumonia (CAP) raise methodological...

Deep learning and radiomics based automatic diagnosis of hippocampal sclerosis.

The International journal of neuroscience
Accurate and rapid segmentation of the hippocampus can help doctors perform intractable temporal lobe epilepsy (TLE) preoperative evaluations to identify good surgical candidates. This study aims to establish a radiomics system for the automatic diag...

Deep learning based cervical screening by the cross-modal integration of colposcopy, cytology, and HPV test.

International journal of medical informatics
PURPOSE: To develop and evaluate the colposcopy based deep learning model using all kinds of cervical images for cervical screening, and investigate the synergetic benefits of the colposcopy, the cytology test, and the HPV test for improving cervical...

In vivo detection of head and neck tumors by hyperspectral imaging combined with deep learning methods.

Journal of biophotonics
Currently, there are no fast and accurate screening methods available for head and neck cancer, the eighth most common tumor entity. For this study, we used hyperspectral imaging, an imaging technique for quantitative and objective surface analysis, ...

Deep learning identifies inflamed fat as a risk factor for lymph node metastasis in early colorectal cancer.

The Journal of pathology
The spread of early-stage (T1 and T2) adenocarcinomas to locoregional lymph nodes is a key event in disease progression of colorectal cancer (CRC). The cellular mechanisms behind this event are not completely understood and existing predictive biomar...

Evaluation of the correlation between gaze avoidance and schizophrenia psychopathology with deep learning-based emotional recognition.

Asian journal of psychiatry
OBJECTIVE: To investigate the correlation between gaze avoidance and psychopathology in patients with schizophrenia through eye movement measurements in real-life interpersonal situations.