Search Results for author: Cristian A. Linte

Found 13 papers, 5 papers with code

Investigating the Robustness of Vision Transformers against Label Noise in Medical Image Classification

no code implementations26 Feb 2024 Bidur Khanal, Prashant Shrestha, Sanskar Amgain, Bishesh Khanal, Binod Bhattarai, Cristian A. Linte

Label noise in medical image classification datasets significantly hampers the training of supervised deep learning methods, undermining their generalizability.

Image Classification Medical Image Classification

Medical Vision Language Pretraining: A survey

no code implementations11 Dec 2023 Prashant Shrestha, Sanskar Amgain, Bidur Khanal, Cristian A. Linte, Binod Bhattarai

Medical Vision Language Pretraining (VLP) has recently emerged as a promising solution to the scarcity of labeled data in the medical domain.

Self-Supervised Learning

Improving Medical Image Classification in Noisy Labels Using Only Self-supervised Pretraining

1 code implementation8 Aug 2023 Bidur Khanal, Binod Bhattarai, Bishesh Khanal, Cristian A. Linte

In this work, we explore contrastive and pretext task-based self-supervised pretraining to initialize the weights of a deep learning classification model for two medical datasets with self-induced noisy labels -- NCT-CRC-HE-100K tissue histological images and COVID-QU-Ex chest X-ray images.

Learning with noisy labels Medical Image Classification +1

A Disparity Refinement Framework for Learning-based Stereo Matching Methods in Cross-domain Setting for Laparoscopic Images

no code implementations5 Feb 2023 Zixin Yang, Richard Simon, Cristian A. Linte

Yet, as a large laparoscopic dataset for training learning-based methods does not exist and the generalization ability of networks remains to be improved, the incorporation of the proposed disparity refinement framework into existing networks will contribute to improving their overall accuracy and robustness associated with depth estimation.

Depth Estimation Stereo Matching

Learning Feature Descriptors for Pre- and Intra-operative Point Cloud Matching for Laparoscopic Liver Registration

no code implementations7 Nov 2022 Zixin Yang, Richard Simon, Cristian A. Linte

To assist with this task, we explore the use of learning-based feature descriptors, which, to our best knowledge, have not been explored for use in laparoscopic liver registration.

CNN-based Cardiac Motion Extraction to Generate Deformable Geometric Left Ventricle Myocardial Models from Cine MRI

no code implementations30 Mar 2021 Roshan Reddy Upendra, Brian Jamison Wentz, Richard Simon, Suzanne M. Shontz, Cristian A. Linte

Patient-specific left ventricle (LV) myocardial models have the potential to be used in a variety of clinical scenarios for improved diagnosis and treatment plans.

Image Registration Motion Estimation

L-CO-Net: Learned Condensation-Optimization Network for Clinical Parameter Estimation from Cardiac Cine MRI

1 code implementation21 Apr 2020 S. M. Kamrul Hasan, Cristian A. Linte

In this work, we implement a fully convolutional segmenter featuring both a learned group structure and a regularized weight-pruner to reduce the high computational cost in volumetric image segmentation.

Cardiac Segmentation Image Segmentation +3

CondenseUNet: A Memory-Efficient Condensely-Connected Architecture for Bi-ventricular Blood Pool and Myocardium Segmentation

no code implementations5 Apr 2020 S. M. Kamrul Hasan, Cristian A. Linte

With the advent of Cardiac Cine Magnetic Resonance (CMR) Imaging, there has been a paradigm shift in medical technology, thanks to its capability of imaging different structures within the heart without ionizing radiation.

Cardiac Segmentation Image Segmentation +3

Left Ventricle Segmentation and Quantification from Cardiac Cine MR Images via Multi-task Learning

no code implementations26 Sep 2018 Shusil Dangi, Ziv Yaniv, Cristian A. Linte

Segmentation of the left ventricle and quantification of various cardiac contractile functions is crucial for the timely diagnosis and treatment of cardiovascular diseases.

Left Ventricle Segmentation LV Segmentation +3

Integrating Atlas and Graph Cut Methods for LV Segmentation from Cardiac Cine MRI

no code implementations3 Nov 2016 Shusil Dangi, Nathan Cahill, Cristian A. Linte

Magnetic Resonance Imaging (MRI) has evolved as a clinical standard-of-care imaging modality for cardiac morphology, function assessment, and guidance of cardiac interventions.

LV Segmentation Segmentation

Cannot find the paper you are looking for? You can Submit a new open access paper.