AIMC Topic: Supervised Machine Learning

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SegMatch: semi-supervised surgical instrument segmentation.

Scientific reports Apr 23, 2025
Surgical instrument segmentation is recognised as a key enabler in providing advanced surgical assistance and improving computer-assisted interventions. In this work, we propose SegMatch, a semi-supervised learning method to reduce the need for expen...
Robotic Surgical Procedures Surgery, Computer-Assisted Image Processing, Computer-Assisted Laparoscopy Supervised Machine Learning Humans Surgical Instruments Algorithms
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Ambiguity-aware semi-supervised learning for leaf disease classification.

Scientific reports Apr 23, 2025
In deep learning, Semi-Supervised Learning is a highly effective technique to enhances neural network training by leveraging both labeled and unlabeled data. This process involves using a trained model to generate pseudo labels to the unlabeled sampl...
Plant Diseases Neural Networks, Computer Musa Plant Leaves Algorithms Supervised Machine Learning Deep Learning
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A semi-supervised prototypical network for prostate lesion segmentation from multimodality MRI.

Physics in medicine and biology Apr 22, 2025
Prostate lesion segmentation from multiparametric magnetic resonance images is particularly challenging due to the limited availability of labeled data. This scarcity of annotated images makes it difficult for supervised models to learn the complex f...
Magnetic Resonance Imaging Multimodal Imaging Prostate Supervised Machine Learning Male Prostatic Neoplasms Humans Image Processing, Computer-Assisted Algorithms
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scRSSL: Residual semi-supervised learning with deep generative models to automatically identify cell types.

IET systems biology Apr 22, 2025
Single-cell sequencing (scRNA-seq) allows researchers to study cellular heterogeneity in individual cells. In single-cell transcriptomics analysis, identifying the cell type of individual cells is a key task. At present, single-cell datasets often fa...
Computational Biology Deep Learning Supervised Machine Learning Single-Cell Analysis Humans Neural Networks, Computer
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Tailored self-supervised pretraining improves brain MRI diagnostic models.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Apr 17, 2025
Self-supervised learning has shown potential in enhancing deep learning methods, yet its application in brain magnetic resonance imaging (MRI) analysis remains underexplored. This study seeks to leverage large-scale, unlabeled public brain MRI datase...
Humans Algorithms Deep Learning Magnetic Resonance Imaging Supervised Machine Learning Brain Brain Neoplasms Image Interpretation, Computer-Assisted
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A clinical benchmark of public self-supervised pathology foundation models.

Nature communications Apr 17, 2025
The use of self-supervised learning to train pathology foundation models has increased substantially in the past few years. Notably, several models trained on large quantities of clinical data have been made publicly available in recent months. This ...
Humans Algorithms Benchmarking Supervised Machine Learning Neoplasms
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Self-supervised network predicting neoadjuvant chemoradiotherapy response to locally advanced rectal cancer patients.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Apr 14, 2025
Radiographic imaging is a non-invasive technique of considerable importance for evaluating tumor treatment response. However, redundancy in CT data and the lack of labeled data make it challenging to accurately assess the response of locally advanced...
Rectal Neoplasms Chemoradiotherapy Deep Learning Treatment Outcome Neoadjuvant Therapy Supervised Machine Learning Female Male Humans Tomography, X-Ray Computed
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Joint semi-supervised and contrastive learning enables domain generalization and multi-domain segmentation.

Medical image analysis Apr 12, 2025
Despite their effectiveness, current deep learning models face challenges with images coming from different domains with varying appearance and content. We introduce SegCLR, a versatile framework designed to segment images across different domains, e...
Imaging, Three-Dimensional Algorithms Humans Tomography, Optical Coherence Image Interpretation, Computer-Assisted Deep Learning Supervised Machine Learning
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Semi-supervised temporal attention network for lung 4D CT ventilation estimation.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Apr 10, 2025
Computed tomography (CT)-derived ventilation estimation, also known as CT ventilation imaging (CTVI), is emerging as a potentially crucial tool for designing functional avoidance radiotherapy treatment plans and evaluating therapy responses. However,...
Supervised Machine Learning Four-Dimensional Computed Tomography Lung Lung Neoplasms Humans
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DIPathMamba: A domain-incremental weakly supervised state space model for pathology image segmentation.

Medical image analysis Apr 9, 2025
Accurate segmentation of pathology images plays a crucial role in digital pathology workflow. However, two significant issues exist with the present pathology image segmentation methods: (i) Most fully supervised models rely on dense pixel-level anno...
Image Processing, Computer-Assisted Humans Supervised Machine Learning Algorithms Image Interpretation, Computer-Assisted
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