41 papers with code • 0 benchmarks • 2 datasets
These leaderboards are used to track progress in Lesion Detection
Most implemented papers
MULAN: Multitask Universal Lesion Analysis Network for Joint Lesion Detection, Tagging, and Segmentation
When reading medical images such as a computed tomography (CT) scan, radiologists generally search across the image to find lesions, characterize and measure them, and then describe them in the radiological report.
3D Context Enhanced Region-based Convolutional Neural Network for End-to-End Lesion Detection
3D context is known to be helpful in this differentiation task.
Improving RetinaNet for CT Lesion Detection with Dense Masks from Weak RECIST Labels
We propose a highly accurate and efficient one-stage lesion detector, by re-designing a RetinaNet to meet the particular challenges in medical imaging.
Lesion Focused Super-Resolution
Super-resolution (SR) for image enhancement has great importance in medical image applications.
Reg R-CNN: Lesion Detection and Grading under Noisy Labels
To this end, we propose Reg R-CNN, which replaces the second-stage classification model of a current object detector with a regression model.
A Generalized Deep Learning Framework for Whole-Slide Image Segmentation and Analysis
However, the size of images and variability in histopathology tasks makes it a challenge to develop an integrated framework for histopathology image analysis.
Stroke Lesion Segmentation with Visual Cortex Anatomy Alike Neural Nets
Fast and precise stroke lesion detection and location is an extreme important process with regards to stroke diagnosis, treatment, and prognosis.
FCN-Transformer Feature Fusion for Polyp Segmentation
The resulting features from both branches are then fused for final prediction of a $h\times w$ segmentation map.
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.