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Process diagram of image pre-processing where each step is represented with a block. Block ( A ): artefacts present in the original mammograms are removed using various methods: binary masking, morphological opening, and largest contour detection resulting in artefact free mammograms; ( B ) lines attached to the breast part of the mammograms are removed using various methods: inRange Operation, <t>Gabor</t> <t>filter,</t> Morphological opening, and Invert mask operation; ( C ) image enhancement techniques: Gamma correction, CLAHE, and Green Fire Filter of ImageJ software; and finally in Block ( D ) quality of the enhanced images is verified using image statistical analysis.
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Process diagram of image pre-processing where each step is represented with a block. Block ( A ): artefacts present in the original mammograms are removed using various methods: binary masking, morphological opening, and largest contour detection resulting in artefact free mammograms; ( B ) lines attached to the breast part of the mammograms are removed using various methods: inRange Operation, Gabor filter, Morphological opening, and Invert mask operation; ( C ) image enhancement techniques: Gamma correction, CLAHE, and Green Fire Filter of ImageJ software; and finally in Block ( D ) quality of the enhanced images is verified using image statistical analysis.

Journal: Biology

Article Title: BreastNet18: A High Accuracy Fine-Tuned VGG16 Model Evaluated Using Ablation Study for Diagnosing Breast Cancer from Enhanced Mammography Images

doi: 10.3390/biology10121347

Figure Lengend Snippet: Process diagram of image pre-processing where each step is represented with a block. Block ( A ): artefacts present in the original mammograms are removed using various methods: binary masking, morphological opening, and largest contour detection resulting in artefact free mammograms; ( B ) lines attached to the breast part of the mammograms are removed using various methods: inRange Operation, Gabor filter, Morphological opening, and Invert mask operation; ( C ) image enhancement techniques: Gamma correction, CLAHE, and Green Fire Filter of ImageJ software; and finally in Block ( D ) quality of the enhanced images is verified using image statistical analysis.

Article Snippet: , Gabor Filter , cv2.getGaborKernel() , Kernel size = (5, 5), sigma = 3, theta = 1*np.pi/1, lambd = 1*np. Pi/4, gamma = 0.5, phi = 20 and ktype=cv2.CV_32F.

Techniques: Blocking Assay, Software