Publications by authors named "C Ivan Serra"
Article Synopsis
- Advancements in tomographic imaging have improved diagnostics but face barriers like high radiation and costs, particularly in lower-income areas.
- The review identifies methodologies for creating 3D CT-like images from 2D radiographs, including a focus on specific anatomical regions and the role of various advanced imaging technologies.
- It highlights a significant volume of research, mainly from European and North American institutions, utilizing techniques like convolutional neural networks and generative adversarial networks for synthesizing these images.
Although post-transplant cyclophosphamide (PTCY)-based prophylaxis has become a widely adopted strategy for preventing graft-versus-host disease (GVHD) in 9 out of 10 HLA-mismatched unrelated donors (MMUDs), allogeneic hematopoietic cell transplants (allo-HCTs), data on the safety and efficacy of PTCY in this setting remain limited. This single-center study investigates the outcomes of 94 adults with hematological malignancies undergoing MMUD allo-HCT with PTCY and tacrolimus (Tac) (PTCY-Tac) between 2014 and 2023. The median age was 53 years, and 60.
View Article and Find Full Text PDFObjective: To examine and compare the accuracy of measurements obtained from photogrammetric models versus direct measurements taken on dry skulls, with the aim to verify the feasibility of photogrammetry for quantitative analysis in microsurgical neuroanatomy.
Methods: Two dry human skulls were used. Each was scanned using the dual camera system of a smartphone The selected photos were separately processed using 2 different softwares to create three-dimensional models.
[Protocol for the management of obstructive sleep apnea by Primary Care using the STOP-Bang questionnaire and simplified diagnosis methods as screening tools in the region of Osona, Central Catalonia (Barcelona)].
Semergen
December 2024
Obstructive Sleep Apnea (OSA) is a widespread disease, but usually is an underdiagnosed and undertreated public health problem. Nowadays its study is expensive. Collaboration and involvement of all specialties are necessary, also the implementation of simplified diagnostic methods to try to improve detection, increase the diagnosis and treatment ratio.
View Article and Find Full Text PDFArticle Synopsis
- - The research aimed to create a deep learning model for accurately assessing the extent of resection (EOR) in glioblastoma patients using postoperative MRI scans, addressing limitations of existing algorithms that only focus on preoperative images.
- - Utilizing data from multiple sources, the model was trained to segment tumor features like contrast-enhancing tumor, edema, and surgical cavity, and was compared with other segmentation models, showing high performance in classifying resection categories.
- - The study found that the nnU-Net framework outperformed other algorithms, achieving high accuracy in both segmentation (with median Dice scores up to 0.81) and EOR classification (96% accuracy in comparisons), making it a valuable tool for clinical use.