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Found 2 essays matching the above criteria.

1. 1. Comparing Weak and Strong Annotation Strategies for Multiple Instance Learning in Digital Pathology

   University essay from KTH/Skolan för kemi, bioteknologi och hälsa (CBH)

   Author : Alice Ciallella; [2022]
   Keywords : Multiple-Instance Learning MIL ; prostate cancer; bag creation; digital pathology; binary classification; multiclass classification;

   Abstract : Prostate cancer is the second most diagnosed cancer worldwide and its diagnosis is done through visual inspection of biopsy tissue by a pathologist, who assigns a score used by doctors to decide on the treatment. However, the scoring system, the Gleason score, is affected by a high inter and intra-observer variability, lack of standardization, and overestimation. READ MORE

3. 2. Recognizing Microscopic Structures: Dense Semantic Segmentation of Multiple Histopathological Classes using Fully Convolutional Neural Networks

   University essay from Lunds universitet/Matematik LTH

   Author : Johan Isaksson; [2016]
   Keywords : segmentation; semantic segmentation; dense semantic segmentation; multiple classes; pathology; digital pathology; histopathology; histopathological; prostate cancer; gleason; gleason grading; gleason scoring; image analysis; machine learning; deep learning; artificial neural networks; ANN; convolutional neural networks; CNN; fully convolutional neural networks; Digital Pathology for Optimized Gleason Score in Prostate Cancer; DOGS; Mathematics and Statistics; Medicine and Health Sciences;

   Abstract : In order to alleviate the financial burden on the healthcare sector as well as relax its employees’ workload, there is a need to introduce novel tools that automate some of the tasks that today are performed manually. Especially pathology poses a problem with few pathologists, demanding manual labour and unnecessary work on benign tissue. READ MORE