26423008900 Archives

University of Minho - Dept. of Industrial Electronics - CMEMS
Campus de Azurém 4800-058 Guimarães Portugal | Tel: +351 253 510380 / Fax: +351 253 510189

CMEMS is supported by the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding UIDB/4436/2020, and UIDP/4436//2020.

Blog Archives

Carlos Lima; Carla Rolanda – National Award of Gastroenterology 2019, Sociedade Portuguesa de Gastrenterologia

Carlos Lima; Carla Rolanda – Travel Grant for Best Submitted Clinical Science Abstracts 2019

Carlos Lima; Carla Rolanda – National Scholar Award 2019

Gilberto Rui Nogueira Cunha, orientador Prof. Carlos Lima – UMinho Award “Iniciação na Investigação Científica 2020”

Detection, Segmentation and Classification of Polyps in Colonoscopies with Mask-RCNN Detection, Classification and Segmentation of Polyps in Colonoscopies with Mask R-CNN

Segmentation of surgical tools from laparoscopy images

Automatic Diagnosis of urinary tract abnormalities (ADUTA)

Computer Assisted Diagnosis (CAD) with Enhanced Cognitive Architectures

Healthy Bone Reconstruction through Generative Modeling

Fourier Analysis and Analog Circuits for General Purpose Computing

Hierarchical Classification of Lesions in Wireless Capsule Endoscopy Exams

Deteção automática de lesões no intestino delgado por análise de imagens obtidas por cápsula endoscópica.

Documentation-driven GUI development for integration of image processing libraries

Brain extraction in partial volumes T2*@7T by using a quasi-anatomic segmentation with bias field correction

Automatic Segmentation and Detection of Small Bowel Angioectasias in WCE Images

Microphone Array for Speaker Localization and Identification in Shared Autonomous Vehicles

Detection of bladder cancer with feature fusion, transfer learning and CapsNetsI

Automatic detection of small bowel tumors in wireless capsule endoscopy images using ensemble learning

Clinical performance of a new software to automatically detect Angioectasias in Small Bowel Capsule Endoscopy

Automatic T1 bladder tumor detection by using wavelet analysis in cystoscopy images

Multi-pathology detection and lesion localization in WCE videos by using the instance segmentation approach