Abstract: The shape and size of the placenta are closely related to fetal development in the second and third trimesters of pregnancy. Accurately segmenting the placental contour in ultrasound images ...
Accurate medical image segmentation is crucial in clinical applications. The existing Swin-UNet model overcomes the limitations of traditional Transformers in handling local details and high-frequency ...
As shown below, the inferred masks predicted by our segmentation model trained on the PNG dataset appear similar to the ground truth masks. If you would like to train ...
Brain tumor segmentation is a vital step in diagnosis, treatment planning, and prognosis in neuro-oncology. In recent years, deep learning approaches have revolutionized this field, evolving from the ...
1 School of Electrical and Electronic Engineering, Wuhan Polytechnic University, Wuhan, China 2 School of Computer Science and Technology, Wuhan University of Science and Technology, Wuhan, China ...
ABSTRACT: In this paper, a novel multilingual OCR (Optical Character Recognition) method for scanned papers is provided. Current open-source solutions, like Tesseract, offer extremely high accuracy ...
As shown above, the number of images of train and valid datasets is not so large to use for the training set of our segmentation model. We trained Ovarian-Tumor-3D TensorFlowFlexUNet Model by using ...
Background and objectives: This paper introduces a novel lightweight MM-3DUNet (Multi-task Mobile 3D UNet) network designed for efficient and accurate segmentation of breast cancer tumors masses from ...
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