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Tumor Detection, Classification and Risk Assessment in Digital Mammograms

Thesis Info

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Author

Sadad, Tariq

Program

PhD

Institute

International Islamic University

City

Islamabad

Province

Islamabad.

Country

Pakistan

Thesis Completing Year

2019

Thesis Completion Status

Completed

Subject

Computer Science

Language

English

Link

http://prr.hec.gov.pk/jspui/bitstream/123456789/10564/1/Tariq%20sadad%20iiui%20CS%20thesis%20year%202019.pdf

Added

2021-02-17 19:49:13

Modified

2024-03-24 20:25:49

ARI ID

1676727852272

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Breast cancer (BC) is the highest cause of deaths in ladies around the globe. Woman are unaware in the remote and backward areas of under developed and developing states, that treatment of breast cancer is possible if it is found at an early stage. The casualties of BC can also be reduced, if demographic risk factors of female are evaluated a prior. Due to its nature of complexity, identifying breast irregularity through mammography and/or ultrasonography is a challenging job for radiologists. A more consistent and precise imaging based computer aided diagnosis (CAD) system assists in recognition of breast cancer at initial stage and play a noteworthy role in the classification of suspicious breast lesions. Ultrasonography of breast is acknowledged as the utmost significant support to mammography for patients with palpable masses and unsatisfying results of mammograms especially in case of young female. Therefore, a CAD system is required for breast ultrasound (BUS) images to distinguish malignant and benign cases. This dissertation has two main modules: the first one is CAD system and second one is the risk assessment of BC. In the proposed CAD framework, pre-processing is executed to remove the unwanted area and suppress the noise from the mammography and ultrasonography images. Then segmentation detects the lump in mammograms and BUS images using cascading of Fuzzy C-Means (FCM) and region-growing technique called FCMRG method and marker-controlled watershed transformation respectively. Hyrbrid features extraction technique employing local binary patterns and gray level cooccurance matrix (LBP-GLCM) along with local phase quantization (LPQ) is used for mammography to extract significant information from segmented masses. Morphological features of ultrasound breast lesion are designed to extract various statistical parameters from contour and shape properties. These features are then used to differentiate benign masses from malignant one using support vector machine (SVM), decision tree (DT), K nearest neighbors (KNN), linear discriminant analysis (LDA) and ensemble classifier. The goodness of the proposed CAD model is evaluated through performance measures on Mammographic Image Analysis Society (MIAS), Digital Database for Screening Mammography (DDSM) and Open Access Series of Breast Ultrasonic Data (OASBUD) datasets. The proposed CAD system achieved remarkable accuracy (=98.2%) with hybrid features on MIAS dataset and (=96%) with morphological features on transverse scan of OASBUD dataset. The proposed CAD system can also be implemented for the patients residing in the rural and backward areas to diagnose the scanned images of mammography and ultrasonography and to detect breast anomalies in the nonavailability of expert radiologists and weak cellular coverage. In second module, demographic risk factors of female have been employed to evaluate the risk grade (that is low, moderate, high) in a specific lady under investigation. For this purpose, Adaptive neuro fuzzy inference system (ANFIS) with sub-clustering and FCM is used and achieved high accuracy on the patient data gathered through questionnaire. The outputs of the CAD system can also be used to merge with demographic risk factors of the patients to find the future prediction of possibly occurring breast cancer risk.
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حاجی موسیٰ میاں سملکی (جنوبی افریقا)

حاجی موسیٰ میاں سملکی
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Prospects of Arbuscular Mycorrhizal Technology on Growth, Mineral Nutrient Acquisition and Fixed Oil Profile of Selected Sunflower Helianthus Annuus L. Hybrids at Various Levels of Rock Phosphate in Marginal Soil

The experiment was carried out in a net house in the University of Peshawar Pakistan, to find out the effects of arbuscular mycorrhizal fungi (AMF) inoculation along with application of various levels (0%, 25%, 50% and 100%) of rock phosphate (RP) fertilizer on growth and yield of selected sunflower hybrids (Helianthus annuus L.) in Pdeficient soil. The results revealed that AM fungi effectively promoted the productivity of sunflower hybrids and proved their role as bio-fertilizer. It was noted that dual use of AMF and low-moderate dose of rock phosphate has profound effect regarding plant height, root length, number of leaves/plant, leaf size, head diameter, seed number/ head, seeds weight/head, dry weight of plant, oil content, fatty acid content, mycorrhizal dependency, proximate and mineral composition of the sunflower as compared to control non-inoculated plants. While, at high RP level (RP3) the non mycorrhizal plants outperformed. However the response varied in different hybrids. As far as hybrid response is concerned Hysun-33 performed better in most of the measured aspects as compared to other hybrids. Proximate analysis showed significant (p < 0.05) increase in crude protein, crude fats, moisture, ash and crude fiber content in mycorrhizal plant, however carbohydrates content was reduced. Rock phosphate fertilization showed no significant effect on nitrogen (N), potassium (K) and Zinc (Zn) uptake however phosphorus (P) uptake increases with increasing RP levels in both AMF inoculated and non-inoculated plants. The findings also provided useful information on oil yield and its fatty acid profiles as affected by AMF inoculation. The present study strongly suggests that the AMF-rock phosphate combination produces better results in the enhancement of the oil content of sunflower hybrids even in P-deficient soils. It was noted that the use of AMF along with low doses of rock phosphate promote mono unsaturated (oleic acid) and polyunsaturated fatty acids (linoleic acid), while the use of AMF along with high doses of rock phosphate bring increase in the production of saturated fatty acids like Palmitic acid and stearic acid in sunflower seeds. It has been observed that spore density and AMF root colonization was higher in the soil of control (RP0) plants, which decreases progressively with increasing fertility level, less number of spores and percent root colonization was found at high (RP3) level in all hybrids. Higher P doses declined the sporulation and colonization. Seven AMF species were recorded. The dominant genus was Acaulospora followed by Glomus, Sclerocystis and Gigaspora. The average AMF spore densities ranged from 56-260 spores/ 100gm soil while root colonization ranged from 32-100 %. Mycorrhizal enhancement regarding AMF spore density and root colonization followed RP0>RP1>RP2>RP3 trend in all hybrids. All selected sunflower hybrids were more responsive to mycorrhizal association but degree of dependency also varies according to rock phosphate levels. This study clearly indicates the potential of using indigenous biofertilizer such as AMF for oil seed crops in low fertility soils, to achieve adequate production level with least utilization of synthetic fertilizers for sustainable agriculture practice. The use of biofertilizer is not only eco-friendly but also economical as it reduces our dependence on expensive chemical fertilizers.