79 research outputs found
EFFECT OF LEFT AXIS DEVIATION ON CARDIAC RESYNCHRONIZATION THERAPY RESPONSE IN PATIENTS WITH LEFT BUNDLE BRANCH BLOCK
Uncertainty-informed Mutual Learning for Joint Medical Image Classification and Segmentation
Classification and segmentation are crucial in medical image analysis as they
enable accurate diagnosis and disease monitoring. However, current methods
often prioritize the mutual learning features and shared model parameters,
while neglecting the reliability of features and performances. In this paper,
we propose a novel Uncertainty-informed Mutual Learning (UML) framework for
reliable and interpretable medical image analysis. Our UML introduces
reliability to joint classification and segmentation tasks, leveraging mutual
learning with uncertainty to improve performance. To achieve this, we first use
evidential deep learning to provide image-level and pixel-wise confidences.
Then, an Uncertainty Navigator Decoder is constructed for better using mutual
features and generating segmentation results. Besides, an Uncertainty
Instructor is proposed to screen reliable masks for classification. Overall,
UML could produce confidence estimation in features and performance for each
link (classification and segmentation). The experiments on the public datasets
demonstrate that our UML outperforms existing methods in terms of both accuracy
and robustness. Our UML has the potential to explore the development of more
reliable and explainable medical image analysis models. We will release the
codes for reproduction after acceptance.Comment: 13 page
Evaluation of left ventricular dyssynchrony using combined pulsed wave and tissue Doppler imaging
Thoracic aortic atheroma severity predicts high-risk coronary anatomy in patients undergoing transesophageal echocardiography
Double contrast-enhanced ultrasonography evaluation of preoperative Lauren classification of advanced gastric carcinoma
Subcellular Localization and RNA Interference of an RNA Methyltransferase Gene from Silkworm, Bombyx Mori
RNA methylation, which is a form of posttranscriptional modification, is catalyzed by S-adenosyl-L-methionone-dependent RNA methyltransterases (RNA MTases). We have identified a novel silkworm gene, BmRNAMTase, containing a 369-bp open reading frame that encodes a putative protein containing 122 amino acid residues and having a molecular weight of 13.88 kd. We expressed a recombinant His-tagged BmRNAMTase in E. coli BL21 (DE3), purified the fusion protein by metal-chelation affinity chromatography, and injected a New Zealand rabbit with the purified protein to generate anti-BmRNAMTase polyclonal antibodies. Immunohistochemistry revealed that BmRNAMTase is abundant in the cytoplasm of Bm5 cells. In addition, using RNA interference to reduce the intracellular activity and content of BmRNAMTase, we determined that this cytoplasmic RNA methyltransferase may be involved in preventing cell death in the silkworm
Predicting lymph node status in patients with early gastric carcinoma using double contrast-enhanced ultrasonography
A new baseline scoring system may help to predict response to cardiac resynchronization therapy
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