باتوں سے بھی آگے تری سانسوں میں رہیں گے
دن جب بھی پھرے ہم تری راتوں میں رہیں گے
دوڑیں گے ترے جسم میں ہم بن کے محبت
ہم زندہ ترے عشق حوالوں میں رہیں گے
ہے قحط اگر وصل کا اس دشتِ جنوں میں
ہم ہجر زدہ آس کے ناتوں میں رہیں گے
اے ابرِ محبت! نہ ترا پہلو ملا تو
ہم صیدِ قفس ہجر کی گھاتوں میں رہیں گے
خوشبو ہے کہ سایہ ہے مرا، گل کہ فضاؔ ہے
اک خواب ہے، ہم ایسے ہی خوابوں میں رہیں گے
Molana Shah Hakeem Mohammad Akhter was born in 1923 in Partabgarh UP India. He received Medical Education from Unani Medical College Ellah Abad and Islamic Education under a great saint Shah Abdul Ghani Phoolpuri in Madrasa Bait ul Aloom. He was a born Sofi, an eminent Islamic scholar, a great philanthropist, an established writer and a great reformer. He wrote more than 200 books. He also established an Islamic University, Asharaf ul Madaris. Thousands of scholars are his pupils, followers and disciples. He imparted them both Aloom-e-Shareyat and Tareeqat. In 2001 he founded an Islamic NGO naming “Al-Akhtar trust International” for helping the suffering humanity. During these days society was ridden with un-Islamic trends and practices Shah Hakeem Mohammad Akhter emerged to rooted out these evils from the society. It will not be wrong to say that Shah Hakeem Mohammad Akhter like his spiritu-al mentor (Maulana Ashraf Ali Thanvi) was the real inherent of Ulama-e-deoband. The aim of this article is to present over view of biography and invalua-ble services which he rendered for tasawwuf and noble cause of humanity.
Medical image analysis is very popular research area these days in which digital images are analyzed for the diagnosis and screening of different medical problems. Diabetic retinopathy (DR) is an eye disease caused by the increase of insulin in blood and may cause blindness if not treated in time. Healthy retina contains blood vessels, optic disc and macula as main components but abnormal retina may contain other components and signs as well. An au- tomated system for early detection of DR can save patient’s vision and can also help the ophthalmologists in screening of DR. In this thesis, we develop algorithms for retinal image analysis based on image processing and pattern classification. Image processing techniques are used for retinal image enhancement and pattern recognition is used for classification of DR stages. The proposed system consists of different stages such as preprocessing, compo- nent extraction, candidate region detection, feature extraction and finally the classification. The first phase consists of input retinal image enhancement, noise removal, extraction of main retinal components and candidate lesions detection. We apply Gabor wavelets and Gabor filter banks for lesion detection. The system then extracts features from candidate lesions using four main properties, i.e. shape, color, gray level and statistical. Finally the classifier takes the feature vectors as inputs and grades the input retinal image into dif- ferent stages of DR. We present a hybrid classifier which combines the Gaussian Mixture Model (GMM), Support Vector Machine (SVM) and an extension of multimodel mediod based modeling approach in an ensemble to improve the accuracy of classification. The im- plemented algorithms are tested and evaluated on publicly available retinal image databases using performance parameters such as sensitivity, specificity, positive predictive value and accuracy. The performance improvement of our proposed system is demonstrated by com- paring them with recently proposed and published methods.