activity
20172023
most citedDRGRADUATE: uncertainty-aware deep learning-based diabetic retinopathy grading in eye fundus images

133 citations · 412 across the 16 of their papers we have counts for

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8 papers · 1 filter

cs.CV2023★ 35 cited

MedShapeNet -- A Large-Scale Dataset of 3D Medical Shapes for Computer Vision

Jianning Li, Zongwei Zhou, Jiancheng Yang +154

Prior to the deep learning era, shape was commonly used to describe the objects. Nowadays, state-of-the-art (SOTA) algorithms in medical imaging are predominantly diverging from co…

cs.CV2023★ 3 cited

ExplainFix: Explainable Spatially Fixed Deep Networks

Alex Gaudio, Christos Faloutsos, Asim Smailagic +2

Is there an initialization for deep networks that requires no learning? ExplainFix adopts two design principles: the "fixed filters" principle that all spatial filter weights of co…

cs.CV2023★ 1 cited

CoNIC Challenge: Pushing the Frontiers of Nuclear Detection, Segmentation, Classification and Counting

Simon Graham, Quoc Dang Vu, Mostafa Jahanifar +86

Nuclear detection, segmentation and morphometric profiling are essential in helping us further understand the relationship between histology and patient outcome. To drive innovatio…

cs.CV2018

iW-Net: an automatic and minimalistic interactive lung nodule segmentation deep network

Guilherme Aresta, Colin Jacobs, Teresa Araújo +4

We propose iW-Net, a deep learning model that allows for both automatic and interactive segmentation of lung nodules in computed tomography images. iW-Net is composed of two blocks…

cs.CV2018★ 19 cited

UOLO - automatic object detection and segmentation in biomedical images

Teresa Araújo, Guilherme Aresta, Adrian Galdran +3

We propose UOLO, a novel framework for the simultaneous detection and segmentation of structures of interest in medical images. UOLO consists of an object segmentation module which…

cs.CV2018★ 17 cited

MedAL: Deep Active Learning Sampling Method for Medical Image Analysis

Asim Smailagic, Hae Young Noh, Pedro Costa +6

Deep learning models have been successfully used in medical image analysis problems but they require a large amount of labeled images to obtain good performance.Deep learning model…

cs.CV2017★ 59 cited

Data-Driven Color Augmentation Techniques for Deep Skin Image Analysis

Adrian Galdran, Aitor Alvarez-Gila, Maria Ines Meyer +7

Dermoscopic skin images are often obtained with different imaging devices, under varying acquisition conditions. In this work, instead of attempting to perform intensity and color…

cs.CV2017★ 76 cited

Towards Adversarial Retinal Image Synthesis

Pedro Costa, Adrian Galdran, Maria Inês Meyer +4

Synthesizing images of the eye fundus is a challenging task that has been previously approached by formulating complex models of the anatomy of the eye. New images can then be gene…