Publications by authors named "Bogdan J Matuszewski"
Article Synopsis
- - Colorectal cancer (CRC) is a leading cause of death globally, and early detection of polyps is crucial for reducing mortality and improving diagnostic efficiency.
- - This study introduces a complete validation framework and evaluates various techniques for detecting, segmenting, and classifying polyps, finding that most methods perform well in detection and segmentation but struggle with classification.
- - The research emphasizes the need for further advancements in polyp classification to support clinicians effectively during procedures, proposing a standardized method to assess and compare different approaches in the field.
Colorectal cancer is one of the most common cancers in the world. While colonoscopy is an effective screening technique, navigating an endoscope through the colon to detect polyps is challenging. A 3D map of the observed surfaces could enhance the identification of unscreened colon tissue and serve as a training platform.
View Article and Find Full Text PDFAnalysis of colonoscopy images plays a significant role in early detection of colorectal cancer. Automated tissue segmentation can be useful for two of the most relevant clinical target applications-lesion detection and classification, thereby providing important means to make both processes more accurate and robust. To automate video colonoscopy analysis, computer vision and machine learning methods have been utilized and shown to enhance polyp detectability and segmentation objectivity.
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- Colonoscopy is the best method for screening colon cancer, but some polyps can still be overlooked, impacting early detection and treatment.
- Various computational systems have been suggested to help find these polyps, yet they lack proper evaluation due to limited publicly available annotated data.
- An Automatic Polyp Detection sub-challenge was held at MICCAI 2015 to assess and compare these methods, revealing that convolutional neural networks perform best, but a combination of different approaches can enhance overall results.
Colorectal adenocarcinoma originating in intestinal glandular structures is the most common form of colon cancer. In clinical practice, the morphology of intestinal glands, including architectural appearance and glandular formation, is used by pathologists to inform prognosis and plan the treatment of individual patients. However, achieving good inter-observer as well as intra-observer reproducibility of cancer grading is still a major challenge in modern pathology.
View Article and Find Full Text PDFThe proliferative activity of breast tumors, which is routinely estimated by counting of mitotic figures in hematoxylin and eosin stained histology sections, is considered to be one of the most important prognostic markers. However, mitosis counting is laborious, subjective and may suffer from low inter-observer agreement. With the wider acceptance of whole slide images in pathology labs, automatic image analysis has been proposed as a potential solution for these issues.
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