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Fast Abdomen Organ and Tumor Segmentation with nn-UNet
The medical imaging community generates a wealth of datasets, many of which are openly accessible and annotated for specific diseases and tasks such...
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Abdomen Multi-organ Segmentation Using Pseudo Labels and Two-Stage
Recently, the nnU-Net network had achieved excellent performance in many medical image segmentation tasks. However, it also had some obvious...
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AdaptNet: Adaptive Learning from Partially Labeled Data for Abdomen Multi-organ and Tumor Segmentation
Due to the high costs associated with the labor and expertise required for annotating 3D medical images at the voxel level, most public and in-house...
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Eye-Guided Dual-Path Network for Multi-organ Segmentation of Abdomen
Multi-organ segmentation of the abdominal region plays a vital role in clinical such as organ quantification, surgical planning, and disease...
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Two-Stage Hybrid Supervision Framework for Fast, Low-Resource, and Accurate Organ and Pan-Cancer Segmentation in Abdomen CT
Abdominal organ and tumour segmentation has many important clinical applications, such as organ quantification, surgical planning, and disease...
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Semi-Supervised Learning Based Cascaded Pocket U-Net for Organ and Pan-Cancer Segmentation in Abdomen CT
In clinical practice, CT scans are frequently employed as the primary imaging modality for detecting prevalent tumors arising from the abdominal...
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From Whole-Body to Abdomen: Streamlined Segmentation of Organs and Tumors via Semi-Supervised Learning and Efficient Coarse-to-Fine Inference
Precise and automated segmentation of abdominal organs and tumors is an important research area of medical image analysis. This domain faces three...
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Multi-task Learning Approach for Unified Biometric Estimation from Fetal Ultrasound Anomaly Scans
Precise estimation of fetal biometry parameters from ultrasound images is vital for evaluating fetal growth, monitoring health, and identifying...
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Varroa Mite Detection in Honey Bees with Artificial Vision
The preservation of species is beneficial for the subsistence of life on planet earth. The honey bee, considered a pollinating and food-producing...
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Towards Abdominal 3-D Scene Rendering from Laparoscopy Surgical Videos Using NeRFs
Given that a conventional laparoscope only provides a two-dimensional (2-D) view, the detection and diagnosis of medical ailments can be challenging....
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Soft Humanoid Finger with Magnetic Tactile Perception
The human skin is equipped with various receptors that sense external stimuli and provide tactile information to the body. Similarly, robots require...
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Fast, Low-resource, and Accurate Organ and Pan-cancer Segmentation in Abdomen CT MICCAI Challenge, FLARE 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, Proceedings
This book constitutes the proceedings of the MICCAI 2023 Challenge, FLARE 2023, held in Conjunction with MICCAI 2023, in Vancouver, BC, Canada, on...
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Multi-domain Abdomen Image Alignment Based on Joint Network of Registration and Synthesis
Multi-domain abdominal image alignment is a valuable and challenging task for clinical research. Normally, with the assistance of the image...
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Probabilistic Framework Based on Deep Learning for Differentiating Ultrasound Movie View Planes
Fetal death, infant morbidity and mortality are generally caused by the presence of congenital anomalies. By performing a fetal morphology scan, the...
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Proposal of a Fetal Movement Sharing System Using a Pressure Sensor Array
We propose a novel fetal movement sharing system employing a pressure sensor array-based fetal movement scanner and a display device. The proposed...
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Abstract: Trainable Joint Bilateral Filters for Enhanced Prediction Stability in Low-dose CT
Low-dose computed tomography (CT) denoising algorithms aim to enable reduced patient dose in routine CT acquisitions while maintaining high image...
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Ensemble-based advancements in maternal fetal plane and brain plane classification for enhanced prenatal diagnosis
In the realm of maternal healthcare, accurate fetal plane detection is of paramount importance. This paper introduces a novel approach that leverages...
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An ensemble deep learning framework for foetal plane identification
Antenatal (prenatal) care stipulates periodic monitoring of the foetus in alleviating risk factors and improving pregnancy outcomes. Foetal images...
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A Machine Learning Framework for Fetal Arrhythmia Detection via Single ECG Electrode
Fetal Arrhythmia is an abnormal heart rhythm caused by a problem in the fetus's heart's electrical system. Monitoring fetal ECG is vital to...
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Self Supervised Denoising Diffusion Probabilistic Models for Abdominal DW-MRI
Quantitative diffusion weighted MRI in the abdomen provides important markers of disease, however significant limitations exist for its accurate...