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View article: What Large Language Models Know About Plant Molecular Biology
What Large Language Models Know About Plant Molecular Biology Open
Large language models (LLMs) are rapidly permeating scientific research, yet their capabilities in plant molecular biology remain largely uncharacterized. Here, we present M o B i P lant , the first comprehensive benchmark for evaluating L…
View article: ChronoRoot 2.0: An Open AI-Powered Platform for 2D Temporal Plant Phenotyping
ChronoRoot 2.0: An Open AI-Powered Platform for 2D Temporal Plant Phenotyping Open
The analysis of plant developmental plasticity, including root system architecture, is fundamental to understanding plant adaptability and development, particularly in the context of climate change and agricultural sustainability. While si…
View article: Conformal In-Context Reverse Classification Accuracy: Efficient Estimation of Segmentation Quality with Statistical Guarantees
Conformal In-Context Reverse Classification Accuracy: Efficient Estimation of Segmentation Quality with Statistical Guarantees Open
Assessing the quality of automatic image segmentation is crucial in clinical practice, but often very challenging due to the limited availability of ground truth annotations. Reverse Classification Accuracy (RCA) is an approach that estima…
View article: The transcription factor <scp>NF</scp> ‐ <scp>YA10</scp> determines the area explored by <i>Arabidopsis thaliana</i> roots and directly regulates <i>LAZY</i> genes
The transcription factor <span>NF</span> ‐ <span>YA10</span> determines the area explored by <i>Arabidopsis thaliana</i> roots and directly regulates <i>LAZY</i> genes Open
SUMMARY Root developmental plasticity relies on transcriptional reprogramming, which largely depends on the activity of transcription factors (TFs). NF‐YA2 and NF‐YA10 (nuclear factor A2 and A10) are downregulated by the specific miRNA iso…
View article: Fitting Skeletal Models via Graph-Based Learning
Fitting Skeletal Models via Graph-Based Learning Open
Skeletonization is a popular shape analysis technique that models an object's\ninterior as opposed to just its boundary. Fitting template-based skeletal\nmodels is a time-consuming process requiring much manual parameter tuning.\nRecently,…
View article: Multi-view Hybrid Graph Convolutional Network for Volume-to-mesh Reconstruction in Cardiovascular MRI
Multi-view Hybrid Graph Convolutional Network for Volume-to-mesh Reconstruction in Cardiovascular MRI Open
Cardiovascular magnetic resonance imaging is emerging as a crucial tool to examine cardiac morphology and function. Essential to this endeavour are anatomical 3D surface and volumetric meshes derived from CMR images, which facilitate compu…
View article: Unsupervised bias discovery in medical image segmentation
Unsupervised bias discovery in medical image segmentation Open
It has recently been shown that deep learning models for anatomical segmentation in medical images can exhibit biases against certain sub-populations defined in terms of protected attributes like sex or ethnicity. In this context, auditing…
View article: The long intergenic noncoding <scp>RNA <i>ARES</i></scp> modulates root architecture in Arabidopsis
The long intergenic noncoding <span>RNA <i>ARES</i></span> modulates root architecture in Arabidopsis Open
Long noncoding RNAs (lncRNAs) have emerged as important regulators of gene expression in plants. They have been linked to a wide range of molecular mechanisms, including epigenetics, miRNA activity, RNA processing and translation, and prot…
View article: CheXmask: a large-scale dataset of anatomical segmentation masks for multi-center chest x-ray images
CheXmask: a large-scale dataset of anatomical segmentation masks for multi-center chest x-ray images Open
The development of successful artificial intelligence models for chest X-ray analysis relies on large, diverse datasets with high-quality annotations. While several databases of chest X-ray images have been released, most include disease d…
View article: The transcription factor NF-YA10 determines the area explored by<i>Arabidopsis thaliana</i>roots through direct regulation of<i>LAZY</i>and<i>TAC</i>genes
The transcription factor NF-YA10 determines the area explored by<i>Arabidopsis thaliana</i>roots through direct regulation of<i>LAZY</i>and<i>TAC</i>genes Open
Root developmental plasticity relies on transcriptional reprogramming, which largely depends on the activity of transcription factors (TFs). NF-YA2 and NF-YA10 (Nuclear Factor A2 and A10) are down-regulated by the specific miRNA isoform mi…
View article: Multi-center anatomical segmentation with heterogeneous labels via landmark-based models
Multi-center anatomical segmentation with heterogeneous labels via landmark-based models Open
Learning anatomical segmentation from heterogeneous labels in multi-center datasets is a common situation encountered in clinical scenarios, where certain anatomical structures are only annotated in images coming from particular medical ce…
View article: Improving anatomical plausibility in medical image segmentation via hybrid graph neural networks: applications to chest x-ray analysis
Improving anatomical plausibility in medical image segmentation via hybrid graph neural networks: applications to chest x-ray analysis Open
Anatomical segmentation is a fundamental task in medical image computing, generally tackled with fully convolutional neural networks which produce dense segmentation masks. These models are often trained with loss functions such as cross-e…
View article: ChronoRoot: High-throughput phenotyping by deep segmentation networks reveals novel temporal parameters of plant root system architecture
ChronoRoot: High-throughput phenotyping by deep segmentation networks reveals novel temporal parameters of plant root system architecture Open
Background Deep learning methods have outperformed previous techniques in most computer vision tasks, including image-based plant phenotyping. However, massive data collection of root traits and the development of associated artificial int…
View article: Hybrid graph convolutional neural networks for landmark-based anatomical\n segmentation
Hybrid graph convolutional neural networks for landmark-based anatomical\n segmentation Open
In this work we address the problem of landmark-based segmentation for\nanatomical structures. We propose HybridGNet, an encoder-decoder neural\narchitecture which combines standard convolutions for image feature encoding,\nwith graph conv…
View article: ChronoRoot: High-throughput phenotyping by deep segmentation networks reveals novel temporal parameters of plant root system architecture
ChronoRoot: High-throughput phenotyping by deep segmentation networks reveals novel temporal parameters of plant root system architecture Open
Background Deep learning methods have outperformed previous techniques in most computer vision tasks, including image-based plant phenotyping. However, massive data collection of root traits and the development of associated artificial int…