Notice bibliographique
Résumé
INTRODUCTION Microwave imaging shows potential in medical applications such as tracking breast tumors [1]. It is advantageous over some of the other modalities such as MRI due to its relatively low cost, non-ionizing nature, and non-invasiveness [1]. The Tissue Sensing Adaptive Radar (TSAR) system is developed for microwave breast imaging and acquires reflected signals as an antenna scans the subject at a number of locations [2]. Then, the data is processed and an image is formed using a delay and sum focusing method [2]. The TSAR imaging algorithm involves many parameters, but the effect of each parameter on the image is unclear. Some parameters, such as wave speed (related to permittivity), are difficult to estimate and often inaccurate. A lack of objective image evaluation metrics makes it difficult to determine the magnitude of the effect of a parameter. The structural similarity (SSIM) index is a tool for objective image quality assessment [3]. It is known for its simplicity and relevance to the human visual system [3]. The SSIM index evaluates how similar two images are by modelling the difference as a weighted product of three independent parameters: luminance, contrast, and structure [3]. This study evaluates if the SSIM index is a suitable metric for evaluating microwave breast images. The dominance of each component of the SSIM Index is also investigated. METHODS In this study, the effectiveness of the SSIM index is evaluated by changing parameters in the TSAR imaging algorithm, then comparing the image produced to the known reference image using the built-in MATLAB ssim function. Both simulated data and experimental data are investigated. Parameters investigated include wave speed in different regions (using permittivity) and different methods to reduce the dominant reflection from the skin. RESULTS The SSIM index is observed to be indicative of the degree of similarities in microwave images. In the cases tested, structure generally has been the most dominant component while contrast is often the least dominant component (Figure 1). Maps of local SSIM index, luminance, contrast, and structure values proved useful in identifying areas of change. The SSIM index indicated that skin permittivity has the least effect on imaging while interior permittivity is important to be within 10-15%. These observations match expectations. DISCUSSION AND CONCLUSIONS The SSIM index looks promising as a suitable image quality metric for microwave breast imaging. It provides an objective and numerical method of evaluating similarity and change between different microwave images. In the future, an improved SSIM index could help identify the effect of some parameters in the TSAR algorithm and optimize the imaging process.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».