Bibliographic record
Abstract
Breast cancer is the most frequently diagnosed cancer in women, and early detection of breast cancer is of utmost importance. Screening programs using mammography have been shown to be effective in reducing breast cancer mortality rates. Nevertheless, it is desirable to reduce the number of errors in screening mammography. Among the most commonly missed signs of breast cancer is architectural distortion, where the normal architecture of the breast is distorted with no definite mass visible. In this thesis, new techniques are developed for computer-aided detection of architectural distortion in mammograms. The mammographic image presents oriented texture related to the anatomical features of the breast. The techniques developed in this work analyze the oriented texture patterns in search of signs that may indicate the presence of architectural distortion. A bank of real Gabor filters is used to extract the orientation field associated with the oriented texture in the mammographic image: a study is presented comparing real Gabor filters to other oriented feature detectors. The orientation field is analyzed using phase portraits: several methods for the optimization of phase portrait models are analyzed and evaluated in this thesis. Three methods for the detection of architectural distortion in mammograms are developed in this thesis. In the first method, the orientation field is analyzed using phase portraits; the resulting phase portrait maps are post-processed to detect sites of architectural distortion. A sensitivity of 88% was obtained at 15 false positives per image. The second method incorporates the rejection of oriented features not related to the appearance of architectural distortion, and the use of simulated annealing in the phase portrait analysis stage, resulting in a sensitivity of 84% at 7.8 false positives per image. In the third method. the phase portrait model is modified to prevent the acceptance of patterns where a focal point cannot be reliably identified. A sensitivity of 84% was achieved at 4.8 false positives per image. Improvements in the detection of architectural distortion could increase the rate of detection of early breast cancer, and reduce morbidity and mortality due to breast cancer.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".