Lesion Detection
54 papers with code • 0 benchmarks • 2 datasets
Benchmarks
These leaderboards are used to track progress in Lesion Detection
Most implemented papers
Low-Dose CT with a Residual Encoder-Decoder Convolutional Neural Network (RED-CNN)
Given the potential X-ray radiation risk to the patient, low-dose CT has attracted a considerable interest in the medical imaging field.
An Ensemble Deep Learning Based Approach for Red Lesion Detection in Fundus Images
In this paper we propose a novel method for red lesion detection based on combining both deep learned and domain knowledge.
3D Anisotropic Hybrid Network: Transferring Convolutional Features from 2D Images to 3D Anisotropic Volumes
The focal loss is further utilized for more effective end-to-end learning.
Unsupervised Detection of Lesions in Brain MRI using constrained adversarial auto-encoders
Lesion detection in brain Magnetic Resonance Images (MRI) remains a challenging task.
Liver Lesion Detection from Weakly-labeled Multi-phase CT Volumes with a Grouped Single Shot MultiBox Detector
We present a focal liver lesion detection model leveraged by custom-designed multi-phase computed tomography (CT) volumes, which reflects real-world clinical lesion detection practice using a Single Shot MultiBox Detector (SSD).
Exploring Uncertainty Measures in Deep Networks for Multiple Sclerosis Lesion Detection and Segmentation
We present the first exploration of multiple uncertainty estimates based on Monte Carlo (MC) dropout [4] in the context of deep networks for lesion detection and segmentation in medical images.
Multiple Sclerosis Lesion Synthesis in MRI using an encoder-decoder U-NET
We also demonstrate the usage of synthetic MS lesions generated on healthy images as data augmentation.
ULDor: A Universal Lesion Detector for CT Scans with Pseudo Masks and Hard Negative Example Mining
To address this problem, this work constructs a pseudo mask for each lesion region that can be considered as a surrogate of the real mask, based on which the Mask R-CNN is employed for lesion detection.
Detecting Lesion Bounding Ellipses With Gaussian Proposal Networks
Instead of directly regressing the rotation angle of the ellipse as the common practice, GPN represents bounding ellipses as 2D Gaussian distributions on the image plain and minimizes the Kullback-Leibler (KL) divergence between the proposed Gaussian and the ground truth Gaussian for object localization.
Attentive CT Lesion Detection Using Deep Pyramid Inference with Multi-Scale Booster
Accurate lesion detection in computer tomography (CT) slices benefits pathologic organ analysis in the medical diagnosis process.