Titlebook: Medical Image Understanding and Analysis; 25th Annual Conferen Bart?omiej W. Papie?,Mohammad Yaqub,J. Alison Nobl Conference proceedings 20

AUGER

BACLE

Exploring the Correlation Between Deep Learned and Clinical Features in Melanoma Detectionhree broad kinds of raw pixel-based learning algorithms based on convolution, spatial self-attention and attention as activation were analyzed and compared with the ABCD skin lesion clinical features based learning algorithms, with qualitative and quantitative interpretations.

BROTH

An Efficient One-Stage Detector for Real-Time Surgical Tools Detection in Robot-Assisted Surgeryr than the state-of-the-art detectors. We believe the proposed method is the first to generate ghost feature maps for detecting surgical tools. Experimental results show that the proposed method achieves 91.6% mAP on the Cholec80-locations dataset and 100% mAP on the Endovis Challenge dataset with t

GRATE

A Comparison of Computer Vision Methods for the Combined Detection of Glaucoma, Diabetic Retinopathyrning architecture and SVM classifier, using standard RGB images (labelled as Normal). The other uses retina images with only the green channel present (labelled as Green). The Inception V3 Normal model achieved the best performance with accuracy and an F1-Score of 99.39%. The SqueezeNet Green model

cumber

Prostate Cancer Detection Using Image-Based Features in Dynamic Contrast Enhanced MRIn performance. Evaluation is based on a publicly available dataset. Using image-based features outperforms using either the features extracted from the pharmacokinetic models or the perfusion-related measurements. By applying feature selection to the aggregation of all features, the performance of p

chondromalacia

空中

食品室

Brain-Connectivity Analysis to Differentiate Phasmophobic and Non-phasmophobic: An EEG Studytal results and statistical analysis show that the proposed method shows superior efficacy in estimating the directed brain-connectivity as compared to the very well-known classical Granger Causality, classical CCM and other off-the-shelf brain-connectivity algorithms.

Fabric

埋伏

Data-Driven Speed-of-Sound Reconstruction for Medical Ultrasound: Impacts of Training Data Format anse information of ultrasound data for SoS reconstruction. Our results showed that distortion of the phase information results in inconsistent SoS predictions, indicating sensitivity of the investigated approach to phase information. We demonstrated that without losing significant accuracy, decimated