Predominantly afflicting individuals aged 45 and above, this ailment is commonly labeled as a “wear and tear” joint disorder, targeting joints such as the knee, hand, hips, and spine. Osteoarthritis symptoms typically increase gradually, contributing to the deterioration of articular cartilage. ...
Kim et al. [14] used it as a tool to measure the skeletal muscle index (SMI) in the L3 region of the spine. Neural networks for muscle segmentation on medical images Kanavati et al. [15] detected a slice near the L3 vertebra using a UNet-like network structure, and segmented the ...
effectiveness of HIFU surgery. Results demonstrated the nnU-Net’s commendable performance in the segmentation of uterine fibroids and their surrounding organs. Specifically, 3D nnU-Net achieved Dice Similarity Coefficients (DSC) of 92.55% for the uterus, 95.63% for fibroids, 92.69% for the spine, ...
To accurately identify the spine axis, a further algorithm was developed which identifies the center of the spine using the stored preprocessed image with bone window settings as described in the previous section (Fig. 14a suppl.). A “bone image” slice containing the lung is projected onto ...
Build labeled image uses: docker/build-push-action@v5 with: context: . file: Dockerfile.new push: true labels: ci.digest=${{ steps.docker_build.outputs.digest }} tags: ghcr.io/${{ github.repository }}:${{ github.ref_name }} ...
Systems, methods and computer program products to annotate axial-view spine images with the desired characteristics of not requiring additional views of the spine or cross-referencing features are provided. In one aspect, the disclosed method does not require external training from a manually-labeled ...
However, several challenges still slow down progress in this area of research. As we mentioned, these challenges include the difficulty of training accurate models for diagnosing evolving fetal brain abnormalities, the lack of labeled ultrasound images for certain conditions, etc. Nevertheless, ongoing ...
first proposed a 3D CNN for lung nodule detection using weakly labeled data. In 3D medical imaging, data labeling is quite complex and time-consuming when compared to 2D image modalities. The authors used a single-pixel point to unveil the data and used this single point information to grow ...
3) Each sonographic image is labeled, leaving little to the imagination. 4) A short description is added to each image on the web site. Included are clinical details of the patient and major ultrasound findings of each case. 5) Best of all- the whole gallery of ultrasound images is open...
Object detection in 3-D medical images is often necessary for constraining a segmentation or registration task. It may be a task in its own right as well, when instances of a structure, e.g. the lymph nodes, are searched. Problems from occlusion, illumin