Mark Eramian

A comparison of deep learning performance against health-care professionals in detecting diseases from medical imaging: a systematic review and meta-analysis

Advanced Deep Learning Techniques Applied to Automated Femoral Neck Fracture Detection and Classification

Image analysis and machine learning in digital pathology: Challenges and opportunities

Automatic thyroid nodule recognition and diagnosis in ultrasound imaging with the YOLOv2 neural network

Deep learning for digital pathology image analysis: A comprehensive tutorial with selected use cases

Cellpose 2.0: how to train your own model

Identification of tumor epithelium and stroma in tissue microarrays using texture analysis

Preparing Medical Imaging Data for Machine Learning

A survey on deep learning in medical image analysis

Automated histological classification of whole-slide images of gastric biopsy specimens

Spectral analysis for pulmonary nodule detection using the optimal fractional S-Transform

Detection of lobular structures in normal breast tissue

Gastric cancer

A scoping review of transfer learning research on medical image analysis using ImageNet

Application of deep learning technique to manage COVID-19 in routine clinical practice using CT images: Results of 10 convolutional neural networks

Physiological effects of indomethacin and celecobix: anS-transform laser Doppler flowmetry signal analysis

A review of medical image data augmentation techniques for deep learning applications

Support vector machines in remote sensing: A review

Convolutional Neural Networks for Radiologic Images: A Radiologist’s Guide

A Deep Convolutional Neural Network for segmenting and classifying epithelial and stromal regions in histopathological images

Using the one-dimensional S-transform as a discrimination tool in classification of hyperspectral images

Thyroid Nodule Classification in Ultrasound Images by Fine-Tuning Deep Convolutional Neural Network

Segmentation of epithelium in H&E stained odontogenic cysts

Automated classification of four types of developmental odontogenic cysts

Local S-spectrum analysis of 1-D and 2-D data